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STUDIES ON THE RELATIONSHIP AMONG SEED QUALITY TESTS AND
FIELD EMERGENCE OF SUGAR BEETS (Beta vulgaris L.) IN MICHIGAN

By

Marcos De Dimas Morales-Barrios

A THESIS
Submitted to
Michigan State University

in partial fulﬁllment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Crop and Soil Sciences

2000

ABSTRACT

STUDIES ON THE RELATIONSHIP AMONG SEED QUALITY TESTS AND
FIELD EMERGENCE OF SUGAR BEETS (Beta vulgaris L.) IN MICHIGAN

By

Marcos De Dimas Morales-Barrios

Two experiments to evaluate differences in sugar beet seed vigor and the
inﬂuence of seed size on seed/seedling vigor and performance were carried out
both in laboratory and ﬁeld tests in 1998 and 1999. Experiment One utilized
seed lots with a wide range of seed quality, representing different production
years and lengths of storage. Seed lots for Exp. 2 were of high quality
representing three varieties with three different seed sizes. Laboratory tests
used to evaluate seed quality and vigor included standard pleated germination
test, cold test, the high moisture cold test, standard accelerated aging test,
accelerated aging test incubated over NaBr, sand test, and bulk conductivity test.
Field emergence data were collected at Saginaw, Ingham and Huron counties in
1998 and in Saginaw and Ingham counties in 1999.

No single vigor test had the best correlation with ﬁeld emergence over all

planting environments. Combinations of tests in multiple regression equations,

for each soil environment resulted in R2 values between 0.486 and 0.980. The
use of the pleated germination test plus the cold test gave the best indication of

potential ﬁeld emergence under most ﬁeld conditions found in Michigan.

DEDICATION

To all those who believed in me...
Specially to Mr. Cal Bn'cker for all his support, inputs and commitment to this
research, Cal with all my respect, admiration and appreciation this work is
dedicated to you...

ACKNOWLEDGMENTS

I would like to thank my Lord for all the wonderful opportunities I have
enjoyed in life; a wonderful family and this unique experience at Michigan State
University. I also would like to acknowledge the Morales family for teaching me
how to be a good Christian and human being and for their eternal support
throughout my graduate studies. Furthermore, thank you for teaching me to ﬁght
for what I believe in and want from life. Thanks for many years of a wonderful
childhood and giving me the pleasure and joy to have brothers and a sister in
which every one of them are a good example for our society.

I extend my sincerest gratitude to my committee members: Dr. Lawrence
Copeland, Dr. Donald Christenson, Dr. Kenneth Poff, and Dr. Irvin Widders. Dr.
Copeland, I am very grateful for your guidance and for accepting me as a student
despite your retirement plans. You always kept your promise to be more than a
professor, but also a father. Dr. Christenson, thanks for your guidance, your
interesting exchange of ideas and allowing me to use this research project as the
basis for my MS degree. Dr. Widders, thanks for your sincere effort to provide
this research with excellent ideas and to always show an appreciation for Latin
culture. Dr. Poff, you were instrumental in my obtaining this MS degree. Thank
you for your commitment to the endeavor of ensuring that minority students excel
in the "world of science." The Minority Summer Research Program in the Plant
Sciences being just one example of such a commitment. This program provided
me with the opportunity to pursue a graduate degree. Your dedication to

enhancing the number of minorities in the Plant Sciences is admirable!

Dr. Frank Dennis, Dr. Randolph Beaudry, and Dr. Eric Hanson, the
summers that I spent working in your research projects instilled in me an
intellectual curiosity and drive to pursue an MS in Plant Sciences. Dr. Dennis, I
greatly appreciate your conversation with Dr. Copeland in which you convinced
him of my qualiﬁcations and potential to perform with excellence at Michigan
State University, regardless of the results of my Graduate Record Examination
(GRE).

My deepest gratitude also goes to Mario Mandujano and Edward Timm for
sharing their families with me and "looking out" for me in professional and
personal matters as only big brothers would do.

My appreciation is extended to Marcelo Queijo and Hongyu Liu for your
friendship, brotherhood, assistance, suggestions, and always showing me the
"quick way" to do things in the Seed Sciences. Marcelo thanks for never saying
"no" to my questions even if you had to fabricate the answer (just kidding).

Cal Bricker, I am thankful for your excellent work ethics, organizational
skills, dedication, dependability, genuine interest in my research, and always
going the extra mile. Without you these three years would have been longer.

I am grateful to Gary Zehr, Bryan Long, Paul Horny, Dennis Fleischmann
for all their assistance including planting laboratory tests and ﬁeld trials.

The USDA Unit (Dr. Mitchell McGrath, Rick Kitchen, Robert Sims, Peter
Hudy, Missy Stiefel, Yi Yu, Benildo de los Reyes and Cathy Derrico), Crop and
Soil Sciences staff and graduate fellows provided me with technical assistance,

support, and friendship for which I am very appreciative.

Kadir Kizilkaya, Douglas Karcher and Dr. Dennis Gilliland you were an
integral part in the successful completion of the statistical analysis for this project.

I am also very grateful to Monitor Sugar Company, Michigan Sugar
Company and Seed Systems Inc. for their funding, support and collaboration
throughout this research project.

Friends; Hector Ayala, Joaquin Chong, Vladimir Ferrer, Benjamin Grifﬁn,
Sandra Lopez, Edda Martinez, Carmen Medina, Diana Morrobel, Marcel
Montanez, Michael Roberts, Lycely Sepulveda and Edwin Toledo, thanks for
being there during the bad times because anyone is willing to take part in the
good times. Thank you also for being my family throughout the years at MSU.
This master's degree would not have been possible without you. Ms. Jane
Thompson helped me to be passionate for God and life, and enjoy every
moment. She taught me that the only obstacle to fulﬁlling dreams and goals is
death. Thanks to Brittany Biondo, the Biondo and Hammel families for opening
the doors to their loving homes and allowing me to feel welcomed and part of
your family, particularly during those special days that I typically would have
shared with my family. Finally, I am very proud of the professional
accomplishments of Puerto Rican community at MSU. Thanks for maintaining a

sense of culture even though MSU is miles away from our homeland.

vi

TABLE OF CONTENTS

LIST OF TABLES
LIST OF FIGURES
LIST OF APPENDIX TABLES
INTRODUCTION
LITERATURE REVIEW
Seed and Seedling Vigor
Seed Quality and Vigor Testing
Seed Size
Varieties
Soﬂ
Environmental Factors
Plant Depth/Spacing
Seedling Diseases
Seed Treatment
Economic Impact
MATERIALS AND METHODS
Plant Material
Description of Laboratory Tests
Pleated Germination Test
Cold Germination Test
High Moisture Cold Test
Accelerated Aging Test
Saturated Accelerated Aging Test
Conductivity Test
Sand Test
Experiment 1 (Seed Quality)
A. Seed Lots
B. Laboratory Tests

vii

Page

xiii

xiv

10
10
12
13
14
16
20

22
23
23
24
25
25
26
26
28
29
29
29

C. Field Study
Experiment 2 (Seed Sizes)
A. Seed Lots
B. Laboratory Tests
C. Field Study
Experiment 3 (Seed Enhancement)
A. Seed Lots
B. Laboratory Tests
C. Field Study
RESULTS AND DISCUSSION
I. Laboratory Tests
A. Means and Coefﬁcients of Variance
8. Simple Coefﬁcients of Determination
Il. Relationship Between Laboratory Test and Field Emergence
A. Simple Coefﬁcients of Determination
B. Stepwise Multiple Regression Analysis
III. Inﬂuence of seed size in germination and ﬁeld emergence
(Exp. 2)
A. Laboratory Tests
B. Field Emergence
IV. Inﬂuence of Seed Treatment on Field Emergence (Exp. 3)
SUMMARY
l. Laboratory Tests
II. Relationship Between Laboratory Tests and Field Emergence
III. Inﬂuence of Seed Size on Germination and Field Emergence
IV. Inﬂuence of Seed Treatments on Field Emergence
CONCLUSIONS
APPENDIX
REFERENCES

viii

30
33
33
33
33
35
35
35

38
38

B363

67

67
67
68

79
80
81

SSS

LIST OF TABLES

Table Description of Tables Page
Table 1. Seed lots tested in Exp. 1 (Seed Quality) in 1998. 29
Table 2. Seed lots tested in Exp. 1 (Seed Quality) in 1999. 30
Table 3. Farm, soil series and planting dates for ﬁeld studies 31

of sugar beet seed lots in 1998.
Table 4. Soil series, counting dates and days after planting for ﬁeld 32
studies of sugar beet seed lots in 1998.

Table 5. Farm, soil series and planting dates for ﬁeld studies of 32
sugar beet seed lots in 1999.
Table 6. Description of nine seed lots in Exp. 2 (Seed Size) in 1998. 33

Table 7. Organism index values for the three sites for Exp. 3 (Seed 37
Quality) in 1999.

Table 8. Mean, coefﬁcient of variance and range of laboratory test 39
results averaged over all seed lots tested, Exp. 1 (Seed
Quality), 1998.

Table 9. Mean, coefﬁcient of variance and range of laboratory test 40
results averaged over all seed lots tested, Exp. 1 (Seed
Quality), 1998.

Table 10. Mean, coefﬁcient of variance and range of laboratory test 41
results averaged over all seed lots tested, Exp. 2 (Seed
Size).

Table 11. Mean, coefﬁcient of variance and range of seed treatment 42
test results, Exp. 3 (Seed Enhancement).

Table 12. Laboratory test results for the 20 seed lots in Exp.1 (Seed 44
Quality), 1998.

Table 13.

Table 14.

Table 15.

Table 16.

Table 17.

Table 18.

Table 19.

Table 20.

Table 21.

Table 22.

Table 23.

Laboratory test results for the 20 seed lots in Exp.1 (Seed
Quality), 1999.

Laboratory test results for the nine seed lots tested in Exp.
2 (Seed Size).

Laboratory test results for the ﬁve seed treatments in Exp.
3 (Seed Enhancement), 1998 and 1999.

Simple coefﬁcients of determination r2 among laboratory
test results for Exp. 1 (Seed Quality), 1998.

Simple coefﬁcients of determination r2 among laboratory
test results for Exp. 1 (Seed Quality), 1999.

Simple coefﬁcients of determination r2 among laboratory
test results for Exp. 2 (Seed Size).

Simple coefﬁcients of determination r2 between laboratory
test results and % ﬁeld emergence as inﬂuenced by
location for Exp. 1 (Seed Quality), 1998.

Simple coefﬁcients of determination r2 between laboratory
test results and % ﬁeld emergence as inﬂuenced by
location for Exp. 1 (Seed Quality), 1999.

Simple coefﬁcients of determination r2 between laboratory
test results and % ﬁeld emergence as inﬂuenced by
location for Exp. 2 (Seed Size), 1998.

Simple coefﬁcients of determination r2 between laboratory
test results and % ﬁeld emergence as inﬂuenced by
location for Exp. 2 (Seed Size), 1999.

Independent variables signiﬁcantly contributing (p50.05) to
a stepwise multiple regression equation of laboratory test
and the dependent variable % ﬁeld emergence (mean of
all sowing occasions) and the coefﬁcients of multiple
coefficients of determination for these equations, as
inﬂuenced by location for 1998, Exp. 1 (Seed Quality).

45

46

46

50

51

52

55

56

57

58

62

Table 24.

Table 25.

Table 26.

Table 27.

Table 28.

Table 29.

Table 30.

Independent variables signiﬁcantly contributing (p50.05) to
a stepwise multiple regression equation of laboratory tests
and the dependent variable % ﬁeld emergence (mean of
all sowing occasions) and the coefﬁcients of multiple
coefficients of determination for these equations, as
inﬂuenced by location for 1999, Exp.1 (Seed Quality).
Independent variables signiﬁcantly contributing (p50.05) to
a stepwise multiple regression equation of laboratory tests
and the dependent variable % ﬁeld emergence (mean of
all sowing occasions) and the coefﬁcients of multiple
coefﬁcients of determination for these equations, as
inﬂuenced by location for 1998, Exp. 2 (Seed Size).
Independent variables signiﬁcantly contributing (p50.05) to
a stepwise multiple regression equation of laboratory tests
and the dependent variable % ﬁeld emergence (mean of
all sowing occasions) and the coefﬁcients of multiple
coefﬁcients of determination for these equations, as
inﬂuenced by location for 1999, Exp. 2 (Seed Size).

Multiple coefﬁcients of determination (R2) for regression
equations having Pleated Test 10-d count and Cold Test
10—d count as the independent variables predicting % ﬁeld
emergence for Exp. 1 (Seed Quality).

Multiple coefﬁcients of determination (R2) for regression
equations having Pleated Test 10-d count and Cold Test
10-d count as the independent variables predicting % ﬁeld
emergence for Exp. 2 (Seed Size).

Seedling germination as inﬂuenced by seed size and
variety in laboratory tests.

Seedling emergence as inﬂuenced by seed size, variety,
location and days after planting in1998.

xi

62

63

63

64

69

70

Table 31. Seedling emergence as inﬂuenced by seed size, variety 71
and time of planting in 1999.

xii

Figure

Figure 1.

Figure 2.

Figure 3.

LIST OF FIGURES

Description of Figures

The effect of seed size on conductance for the three
varieties tested on Exp. 2.

Inﬂuence of seed treatments and time of planting on ﬁeld
emergence for Exp. 3 in 1998

Effect of seed treatments on seedling emergence from
soils infested with different level of Aphanomyces spp.

xiii

Page

49

73

77

Table

Table A1 .

Table A2.

Table A3.

Table A4.

Table A5.

Table A6.

Table A7.

Table A8.

LIST OF APPENDIX TABLES

Description of Tables

Analysis of variance for the pleated germination, cold and
sand test results for Exp. 1 (Seed Quality), 1998 as
inﬂuenced by variety, time of count and replication.
Analysis of variance for the accelerated aging test results
for Exp. 1 (Seed Quality), 1998 as inﬂuenced by variety,
time of count and replication.

Slicing procedure for the interaction effect between variety
and time of count for the pleated germination test in Exp. 1
(Seed Quality), 1998.

Slicing procedure for the interaction effect between variety
and time of count for the cold test in Exp. 1 (Seed Quality),
1998.

Slicing procedure for the interaction effect between variety
and time of count for the accelerated aging test in Exp. 1
(Seed Quality), 1998.

Slicing procedure for the interaction effect between variety
and time of count for the sand test in Exp. 1 (Seed
Quality), 1998.

Analysis of variance for the pleated germination, cold, high
moisture cold and conductivity test results for Exp. 1 (Seed
Quality), 1999 as inﬂuenced by variety, time of count and
replication.

Analysis of variance for the pleated germination, cold, high
moisture cold and sand test results for Exp. 2 (Seed Size)
as influenced by variety, seed size, time of count and
replication.

xiv

Page
87

87

88

89

90

91

92

92

Table A9.

Table A10.

Table A1 1.

Table A12.

Table A13.

Table A14.

Table A15.

Table A16.

Table A17.

Table A18.

Analysis of variance for the pleated, cold and sand test
results for Exp. 2 (Seed Size) as inﬂuenced by variety,
seed size, time of count and replication.

Slicing procedure for the interaction effect between variety
and seed size for the pleated germination test in Exp. 2
(Seed Size).

Slicing procedure for the interaction effect between variety
and germination time for the sand test in Exp. 2 (Seed
Size).

Slicing procedure for the interaction effect between variety
and aging time for the accelerated aging test in Exp. 2
(Seed Size).

Slicing procedure for the interaction effect between variety
and time of aging the accelerated aging test over NaBr in
Exp. 2 (Seed Size).

Analysis of variance for pleated germination and cold test
results for Exp. 3 (Seed Enhancement) in 1998 as
inﬂuenced by treatment, time of count and replication.
Analysis of variance for pleated germination and cold test
results for Exp. 3 (Seed Enhancement),1999 as inﬂuenced
by treatment, time of count and replication.

Multiple comparison and mean separation for the
conductivity test in Exp. 2 (Seed Size).

Multiple comparison and mean separation for the different
planting dates and stand counts conducted in Exp. 3
(Seed Enhancement), 1998.

Multiple comparison and mean separation for the different
sites and stand counts conducted in Exp. 3 (Seed
Enhancement), 1999.

93

94

94

95

95

96

100

Table A19.

Table A20.

Daily maximum and minimum soil temperatures (°C) and
precipitation (mm) at the three ﬁeld testing locations in
1998.

Daily maximum and minimum soil temperatures (°C) and
precipitation (mm) at the three ﬁeld testing locations in
1999.

102

104

INTRODUCTION

Sugar beets are an important agronomic crop in Michigan, accounting for
10.2% of the United States production in 1997. Over 71,000 hectares were
planted in 1998, representing an eight percent increase from the previous year.

While the cost of sugar beet seed is only about eight percent of the total
production costs per hectare, the results of planting poor quality seed are more
costly. Replanting costs of $70-$75 ha, along with the increased labor, soil
compaction, and possible decrease in yield due to delayed planting can
drastically reduce the net income from a sugar beet crop.

Recommendations for early planting and increased acreage of sugar
beets in Michigan is thought to have increased the possibility of poor ﬁeld
emergence resulting from the planting of low quality seed. The lack of
emergence of sugar beet seedlings and of successful stand establishment are
often major factors limiting sugar beet production.

Seedling emergence requires the utilization of stored seed reserves to
produce elongation of both the hypocotyl and radicle. Energy supply and
seedling development are a result of catabolism and metabolism that are
inﬂuenced by the soil environment. The state of the soil environment determines
the efﬁciency of energy conversion into the expansive growth of the plant axis.
During the many years in which multigerm seed was planted, no particular
germination problems were encountered, unless the seed was damaged by
insects. However when monogerm seed was introduced in the early 1950’s, both

germination and ﬁeld emergence were reduced due to the nature of the single

germ seed type. This has led many growers and agronomists in the sugar beet
industry to question the fundamental quality of monogerm relative to multigerm
seed.

Commercial sugar beet seed is now routinely processed and graded to
give a standard germination exceeding 90.0%. Field emergence, however, is
often much lower than that potential. Consequently, accurate ways are needed
to predict the performance of individual sugar beet seed lots in the ﬁeld.
Because of similar concerns in a wide range of crops, vigor tests to supplement
the standard germination test have been frequently suggested by seed
companies and growers because of the tendency for the standard germination
test to overestimate ﬁeld performance under most planting conditions (Delouche
and Baskin, 1973; Delouche and Coldwele, 1960; Woodstock 1973; Yacklich et.
al, 1979; Kraak et. al, 1984; and Lovato and Cogalli, 1992).

The many different factors that affect vigor and the variable conditions
under which vigor tests may be performed in different seed laboratories, as well
as the inﬁnite array of seedbed conditions into which sugar beet seed is planted,
have confounded research efforts to determine which vigor tests best predict ﬁeld
emergence results. This study was initiated with three major objectives: First, to
evaluate which of several established seed testing procedures best determines
ﬁeld emergence and stand establishment in seedbed conditions in Michigan.
The second objective was to determine seed quality levels of seed lots from

various years and varieties and evaluate their performance in ﬁeld emergence

and stand establishment. The ﬁnal objective was to evaluate the effect of seed

size and chemical seed treatments on seed/seedling vigor and ﬁeld performance.

LITERATURE REVIEW

Seed and Seedling Vigor

Seed scientists have for many years accepted the concept of
seed/seedling vigor as a seed quality factor. Within the last three decades it has
also become a vital part of the quality control and marketing programs of many
commercial seed companies.

According to Perry (1972), one of the earliest recognitions of vigor
differences in seed was by Nobbe in 1876, who used the term "energy of
germination." However, most of the research on vigor and vigor testing has been
done in the last 35 years. In 1950, Franck used the term "vigor" in describing his
work with soil germination tests at a meeting of the lntemational Seed Testing
Association (ISTA) (Perry, 1972). Seven years later Isley (1958) talked to
members of the Association of Ofﬁcial Seed Analysts (AOSA) about vigor and
vigor testing. Since then a great many papers have been published on this
subject.

The expression of vigor can be described from two different viewpoints.
Some researchers speak of seed vigor per se as an intrinsic property of the seed
(Woodstock, 1973). Perry (1972) referred to vigor along with viability, seed
health, structural soundness and size as seed quality components. Heydecker
(1972) concluded that a population of seeds cannot be classiﬁed as being only
good or bad, but in having a level of vigor that provides a continuum from poor to

good.

The vigor of harvested seeds in storage has been called storage vigor
(Heydecker, 1969), the vigor of the storage life of the seed (Bradnock, 1975) and
the non-active vigor state (Heydecker, 1972). Descriptions of the totality and
speed of germination in the absence of environmental inﬂuences have included
the terms germination vigor (Heydecker, 1969), germination energy (Moore,
1963), germination capacity (Schoorel, 1956) and the intensity factor
(Woodstock, 1969). These terms imply the importance of seed viability in
describing seed vigor. Delouche (1974) concluded that vigor only relates to
viable seeds, because a seed that does not germinate has no vigor potential.

The results of the interaction between the seed/seedling and
environmental inﬂuences such as temperature, moisture, soil crusting and
pathogenic microorganisms is the second way vigor can be expressed. Vigorous
seeds/seedlings have a greater capacity for germination and emergence when
subjected to adverse environmental conditions. These seeds/seedlings are said
to have a higher ﬁeld survival rate (Heydecker, 1972), a larger environmental
range factor (Woodstock, 1969) or a better stand establishment capacity
(Delouche and Caldwell, 1960). Once the seedling stand is established, the
seedling survival rate (Bradnock, 1975) and seedling growth can be measured.
Thus, seedling vigor (Heydecker, 1969) on an individual plant basis can have a
major effect on the competitive interactions between plants (Pollock and Roos,
1972) and ultimately on yield potential (Bradnock, 1975).

Although the concept of seed and seedling vigor has been widely

accepted, there was not a general agreement on a precise definition of vigor for

many years. Investigators have deﬁned vigor to coincide with their own
understanding and experiences. lsely (1957) deﬁned seed vigor as "the sum
total of all seed attributes which favor stand establishment under favorable
conditions." Building on this deﬁnition, Delouche and Caldwell (1960) stated that
seed vigor is "the sum of all seed attributes which favor rapid and uniform stand
establishment." Woodstock (1965) proposed that seed vigor was "that condition
of good health and natural robustness in seed, which, upon planting, permits
germination to proceed rapidly and to completion under a wide range of
environmental conditions." Eight years later, Perry (1978) identiﬁed seed vigor
as physiological property determined by the genotype and modiﬁed by the
environment which governs the ability of a seed to produce a seedling rapidly in
soil and the extent to which the seed tolerates a range of environmental factors."
By this time a consensus was rapidly emerging on a deﬁnition of seed vigor. In
1977, ISTA deﬁned vigor as "the sum total of those properties of the seed which
determinates the potential level of activity and performance of the seed or seed
lot during germination and seedling emergence (Perry, 1978)." In 1979, AOSA
deﬁned the term as "the sum total of all those properties in seeds which, upon
planting, result in rapid and uniform production of healthy seedlings under a wide
range of environment including both favorable and stress conditions (McDonald,
1980)." Each deﬁnition is unique, but all deal with ﬁeld performance potential.
Thus, this parameter is the ultimate result of vigor, regardless of whether the
vigor expressed is an intrinsic seed property or a result of seed/seedling

interaction with the environment.

The AOSA definition of vigor was adopted for the planning and evaluation

of this study.

Seed Quality and Vigor Testing

The ﬁrst uniform method for conducting sugar beet seed germination tests
was proposed by Skudema and Doxtator (1938). They suggested reporting
results of tests at the end of 10 d and supplementing laboratory tests with ﬁeld
tests wherever possible so as to determine vigor of seedlings as well as plants.
Also, the scientists suggested that the choice of germinating beet seeds at a
continuous temperature of 200°C would better predict ﬁeld emergence.
However, ﬁeld emergence of a seed lot is dependent both on seed quality
(Heydecker, 1969) and upon the environmental factors encountered by the seed,
including temperature (Bierhuizen and Wagevoort, 1974), availability of oxygen
(COme and Tissaou, 1973), moisture (Keller, 1972), disease pressure (Baker and
Rush, 1988; Rush, 1987) and sowing depth. Although a major component of
seed quality is the germination capacity, it is a matter of continuing debate
whether germination percentage measured under optimal conditions provides the
best assessment of the performance potential of the seed in the ﬁeld. Failure of
germination percentage to relate to ﬁeld emergence led to the term vigor. Seed
lots are said to posses low vigor when ﬁeld emergence is poor in comparison to
other seed lots with comparable test germination percentages ('seed lot' for these
studies refers to a particular amount of seed from which subsamples are drawn
and used in the various tests). Differences in seed vigor caused by

environmental conditions during seed development, harvesting procedures and

storage conditions may exist among seed lots having similar warm (standard)
germination results. Planting in a pathogen-infested seedbed under cold
temperatures and/or moisture stress can magnify the expression of these vigor
differences.

Studies in recent years have approached the "vigor question" by trying
different kinds of tests or seed treatments, including excess water stress (Perry,
1978), cold tests (Akeson and Widner, 1980; Kraak et al.; 1984), accelerated
aging and conductivity tests (Kraak et al., 1984; Durrant and Loads, 1990). The
good relationship between percentages of normal seedlings at the ﬁrst count, i.e.
from fourth to tenth day of standard germination and ﬁeld performance has been
noted (Orioli et al., 1979; Herzog, 1980; Orioli and Rosso, 1982).

Since the development of the cold test in the 1940's, seed scientists have
been searching for better ways to measure this complex quality factor called
vigor. Many different types of vigor tests have been proposed. Those adopted
by the seed industry have been promoted as aides to the farmer for selecting
only the highest quality seed lots available and thus maximizing field stand
establishment.

Seed vigor is a complex concept that cannot be measured as easily as a
single property like germination. Most researchers believe that no single test can
adequately measure seed vigor and ﬁeld performance across a wide range of
seed quality and ﬁeld conditions. Thus, a combination of physiological and

biochemical indices has been suggested for improving the accuracy of predicting

ﬁeld performance of a given seed lot (Ching et al., 1977; Edje and Burris, 1971;

and Egli and TeKrony; 1979).

Seed Size

The monogerm sugar beet "seed" is in reality an indehiscent fruit (utricle)
containing a single seed with the perianth attached. A seed lot at harvest
comprises a wide range of fruit size, maturity, and other characteristics because
of the indeterminate growth habit of the sugar beet plant (Scott et al., 1974).
Fruit of commercial seed lots are polished, graded, sorted for shape and gravity
separated. The Michigan Sugar Company grades seed into four sizes, 2 (0.26 -
0.30-cm), 3 (0.30 - 0.34-cm), 4 (0.34 - 0.38-cm), and 5 (0.38 - 0.42-cm).
According to Longden (1986), the most important factors that signiﬁcantly affect
the quality of sugar beet seed are its size and emergence capacity. Seed size
has been shown to inﬂuence germination and ﬁeld emergence (Lexander, 1981,
Akeson, 1981). Seed grown in northern Europe was found to be larger in size
compared to that grown in southern Europe due to the greater amount of cortex
and not because of differences in true seed weight (Longden, 1986). Savitsky
(1954) showed that with monogerm varieties, the weight of the true seed
increased proportionally with the weight of the entire unconditioned fruit. With
most crops, early growth is related to seed size but ﬁnal yield is seldom affected
(Black, 1959, Bleasdale, 1966) because inter-plant competition develops earlier
between the larger plants from large seed. Large seeds had better germination
and emergence compared to small seeds (Snyder and Filban, 1970) but large

size did not necessarily result in good emergence since seeds produced under

low temperatures were large because of thick fruit walls and did not germinate
well (Lexander, 1981 ). TeKrony and Hardin (1968) claim that the major cause of
variable and poor seedling emergence is the occurrence of seedless fruits
(lacking ovules) and those containing underdeveloped seeds, which might be
less frequent in larger seed grades if size is some index of extent of
development. Scott et al. (1974) reported that seedling size and root/shoot ratio
increased with increasing seed size. Furthermore, the largest seeds resulted in
increased sugar yields compared to smaller ones. McLachlan (1972) also
presented evidence that the size of monogerm seed had a strong positive effect
on ﬁnal root yield but no effect on sugar content. Although his results suggested
strong maternal effects on sugar beet root yield, no conclusions were drawn on

the genetic relationship between seed size and root yield.

Varieties

One of the largest causes of variation in emergence in sugar beets
appears to be varieties, where ranges of 20.0 - 30.0% in emergence have been
noted (Steen, 1987). Highly productive monogerm varieties are available, but
improvements are still needed to give higher and better emergence under a wide

range of growing conditions.

Soil

Stehlik and Neuwirth (1928) studied stand establishment as a
comprehensive problem and treated the ecological soil conditions as the most
important factor affecting emergence and seedling survival. The correlation

between germination capacity and ﬁeld emergence declines when soil conditions

10

become less favorable. Seed lots that systematically perform poorly relative to
other lots of the same species when ﬁeld cenditions deteriorate are by deﬁnition
of lower vigor (Perry, 1978). Yonts et al. (1983) reported that soil temperatures
affect the rate of emergence, but not the ﬁnal number of plants which emerge.
This linear relationship developed from the laboratory emergence indicates that
maintenance of soil moisture tensions of less than six atmospheres would ensure
an emergence rate of 60.0% or more. Hunter and Dexter (1950) reported that
air-dry segmented sugar beet seeds germinated only at between 12 and 20.0%
soil moisture. They observed that an additional small amount of water in contact
with the seed induced germination in soils drier than the critical soil moisture of
12.0%. Hunter and Erickson (1952) plotted the minimum soil moisture
percentages required for germination of seeds of various species in several soils
on a moisture tension curve for each soil and found the maximum moisture
tension which produced satisfactory germination was constant at 3.5-
atmospheres for sugar beets. They concluded that greater attention should be
paid to the soil moisture conditions when sugar beets are planted since they
require considerably more moisture for germination than other crops.

Another factor which may have an important inﬂuence on germination and
emergence of sugar beet seedlings is soil compaction. The extent of compaction
of the plow layer is mainly determined by the soil moisture content, the wheel
track distribution, the number of passes by the wheels, the load on the wheels,
the wheel arrangement and characteristics including the tire pressure (Ljungars,

1977). Because of its effect on aeration, compaction of the soils in the seedbed

11

undoubtedly has some effect on emergence, however, available references do
not fully explain the effects of this factor. Emergence is also reduced by the
presence of soil crusts that can form naturally under the effect of rain followed by
drying by sun and/or wind. However, the impact of crusting can be reduced
either by methods of preparing soils, removing the risk of subsequent formation
of crusts, or by selecting varieties capable of exerting greater growth forces

(Goyal, 1982).

Environmental Factors

Wind erosion is a major problem in the establishment of sugar beets in
some areas. Sugar beet seedlings are more vulnerable during the establishment
period when wind speed is the highest, i.e., May and June. Cultural methods
that leave residues on the surface appear to have the greatest potential for
combating the effects of erosion problems.

Snyder and Zielke (1973) showed that the rate of imbibition of sugar beet
seed was related to their sensitivity to excess water. They suggested that to
obtain reliable germination and emergence data, the quantity of water available
to the seed must be rigidly controlled.

Wanjura and Buxton (1972) developed a systematic procedure for
developing seedling emergence models. They developed a model to describe
cotton seed water uptake during imbibition and hypocotyl elongation until
emergence. Laboratory experiments were used to deﬁne the values of the

environmentally—dependent coefficients of selected soil parameters in the model.

In validation tests, the model predicted radicle emergence time within i nine

12

percent. Hypocotyl elongation was not signiﬁcantly different from observed
values in nine often comparisons done by the authors.

Many studies suggest that the pre—emergence seedling growth stages are
sensitive to very wet conditions. Thus, increased risk is associated with early
sowings and many of the post-germination losses probably result from
waterlogging. Possible approaches to minimize this problem include more
tolerant varieties (Durrant, et al., 1984), pre-treating the seeds (Heydecker and
Coolbear, 1977; Akeson, et al., 1981) and the avoidance of excessive soil

compaction.

Planting Depth/Spacing

Yield of sugar beet is similar whether planted to stand or planted more
thickly and hand thinned when grown in 55.0 to 76.0-cm rows at population
density of 10,000 - 16,000 plants/ha (Fomstrom, 1980). Planting to stand
(desired plant populations) has been successful in 76.0-cm rows as well as 56.0-
cm rows if the plant populations are maintained (Cattanach and Schoeder, 1980;
Fomstrom and Jackson, 1983; Winter and Wiese, 1977). Planting depths greater
than 2.5 cm appear to reduce the emergence of sugar beet seeds (Cattanach et
al., 1979; Fomstrom and Miller, 1987). Four to six percent higher emergence
was obtained when using a 1.9-cm seeding depth compared to a 3.2-cm seeding
depth, but the results were not always consistent (Fomstrom and Miller, 1989).
Also, more sugar beet seedlings emerged and at a faster rate as the depth of

seeding decreased from 4.5 to 1.6 cm. Herbicide injury to sugar beet seedlings

13

increased as depth of seeding increased to more than to 2.5 cm (Wilson et al.,

1990).

Seedling Diseases

Stehlik and Neuwirth (1928) concluded that the most critical period during
planting and stand establishment is usually from the time of seed swelling to the
four-leaf stage, during which the young seedlings are very vulnerable to fungal
attack. However, it is primarily the suitable ecological conditions that enable the
seed to germinate and emerge. Sugar beet is susceptible to numerous
seed/seedling diseases, expressed as seed decay, pre-emergence damping—off,
post-emergence damping-off and infection of the radicle and hypocotyl of
emerged plants. The severity of the diseases is inﬂuenced by the susceptibility
of the host, the inoculum potential of the pathogen, environmental factors,
(including temperature, moisture, and soil characteristics) and the effectiveness
of control measures.

Seedling infection by Phoma is often called "black leg." Infection by
Aphanomyces is often referred as "black root." Because of possible confusion of
black leg and black root and the imprecise use of these terms, use of the generic
name of the pathogen is preferable in identifying seedling diseases, e.g., Pythium
damping-off, Rhizoctonia damping-off, Aphanomyces (or beet water mold)
seedling disease, and Phoma seedling infection.

Pythium ultimum Trow is present to some extent in nearly all arable soils
and attacks unprotected seedlings at all temperatures favorable for the

germination of beet seed. The pathogen is favored by high moisture and attacks

14

seedlings of many other crops, causing pre-emergence damping-off. Post-
emergence damping-off may follow under moist soil conditions.

Pythium aphanidermatum (Edson) Fitzp., a high-temperature fungus,
attacks seedlings only in warm soils with abundant soil moisture.

Rhizoctonia solani Kilhn causes some pre-emergence death of seedlings
but inﬂicts most of its damage on emerged seedlings. Infection is initiated below
the soil surface and extends up the hypocotyl, with a distinct margin between
infected and healthy tissue. Lightly infected seedlings often survive and may
produce nearly normal roots. The same fungus, however, may later in the
season cause crown rot or dry rot canker on maturing roots.

Seedlings infected by Aphanomyces cochlioides Drechs. can usually be
distinguished from those infected by Phoma betae or Pythium spp. because the
entire hypocotyl becomes thin and black, with cotyledon necrosis at the base.
Seedlings attacked but not killed by P. betae or Pythium sp. usually recover
rapidly, but Aphanomyces persists and stunted plants still occur in July. The
fungus can be found on the lateral roots of beet plants in infested ﬁelds
throughout the season. This disease is favored by warm, moist soil and thus
occurs most often in late-sown crops. In Europe, a survey conducted by Asher
and Payne (1989) of randomly selected sugar beet ﬁelds conﬁrmed the presence
of Aphanomyces cochlioides Drechs and Pythium sp. on about one-third of the
ﬁelds tested.

Phoma betae Frank is the only important seed-bome pathogen of sugar

beet seedlings. It ﬁrst appears to a limited extent in the fall as seedling or leaf

15

spot infections and persists through the winter as infections on leaf or crown
tissue. With spring growth and bolting, leaf spots, crown infections and later,
lesions on the seed stalks appear. During periods of rainfall or high humidity,
pycnidia of the fungus exude spores in gelatinous masses. These spores are
readily spread by splashing rain or overhead sprinklers or, when dry, may
become air-bome and by these means, come into contact with developing ﬂoral
parts and result in seed infection. However, the most important period of seed
infection appears to occur during the harvest period. When the seed is ready to
harvest, the seed stalks are cut, swathed and allowed to cure in the ﬁeld for a

period of 10 to 20 d before the actual threshing of the seed.

Seed Treatment

In Europe, an excellent survey by Dunning (1972) showed that plant
pathologists in 13 countries believed that the most important seedling pathogen
of sugar beets was Phoma betae and that effective seed treatments against this
pathogen were indispensable. In the United States, however, the experience has
been less consistent. Prior to the 1930's when most of the seed was imported
from Europe, Phoma seedling disease was quite serious and mercury-based
seed treatments such as diethyl mercuric phosphate (EMP) were commonly used
as the only effective means of control. With the initiation of domestic seed
production in the arid southwest, sugar beet seed was found to be essentially
free from Phoma (Leach, 1940 and 1944), thus allowing attention to be focused
on the soilborne seedling pathogens. After the use of mercury seed treatments

was discontinued, newer often selective fungicidal seed treatments were

16

introduced. However, when domestic seed production was later shifted to
Oregon for the production of non-bolting varieties, some seed lots were again
found to carry considerable amounts of Phoma. Several factors prompted the
reevaluation of the use of EMP. First, attitudes have hardened against the
continued use of mercuric compounds. Secondly, a shorter treatment than 24 h
may be adequate, since a survey of Phoma betae levels in sugar beet seed
(Payne, 1986) suggests that severe infestations are rare. Thirdly, the need for
improved stand establishment has been highlighted (Durrant, Jaggard and Scott,
1984), and studies (Durrant and Leads, 1984, 1987) have indicated that
enhancing the seed by prolonged steeping should help to achieve more rapid
establishment of an adequate number of plants. Therefore, an alternative
treatment with comparable efﬁciency was needed. The candidate chemical,
Thiram (tetra-methyl thiuram disulphide), gave maximum control of deep-seated
infections in several species but only when the seed was steeped in a 0.2%
suspension for 24-h at 300°C (Maude, 1966, 1986; Maude, Vizor and Shuring,
1969) and without being harmful to human health. In a series of experiments
between 1977 and 1979 Byford (1985) conﬁrmed that steeping in Thiram was as
effective as EMP.

Knott (1925) described soaking seed of some vegetables in water to
promote germination and utilization of food reserves, the use of oxygen and the
release of carbon dioxide. Some of the factors which affect this beginning of
growth are, the time (length) of soaking, the temperature of the water, the relative

amount of water, the movement of the water, the amount of water surface

17

exposed to air, the size of the seed and the density of the seed mass. More
Injury due to the loss of soluble food reserves might be expected. However, this
is not the case, probably because of the better supply of oxygen and the removal
of carbon dioxide. Knott ( 1925) concluded that soaking seed of beets in shallow
distilled water for 24 h shows no deﬁnite inﬂuence on later growth and yield. In
1944, Stout and Tolman concluded that synthetic growth-regulating substances
did not give signiﬁcant beneﬁts to seedling emergence, vegetative growth,
sucrose content, purity, or yield of roots per acre. Miyamoto and Dexter (1960)
reported that monogerm seed need more moisture to germinate than multigerm
seed. In another study (Dexter and Miyamoto 1959), they found moisture uptake
and emergence to be accelerated if the sugar beet seed balls were coated with
hydrophilic colloids.

In the late 1970's and early 1980's, the so-called "crop success" that
70.0% of the seeds sown must give harvestable roots was still not achieved.
Durrant and Scott (1981) stressed the possibility of improving stand
establishment by making the seed more tolerant to sub-optimal conditions in the
seedbed environment by treating it under controlled conditions before sowing.
Such treatments have utilized various combinations of water, different salts,
sugars or polyethylene glycol solutions with steeping, wetting and drying cycles,
vigorous bubbling, etc. The treatments were divided into two types - those which
"advance" seed (Genkel, 1946; Austin, Longden, and Hutchinson, 1969;
Longden, 1971) and those which "prime" seed (Heydecker, 1974). Both

treatments increase the rate of germination, however, during "advancement" all

18

seeds are affected equally so there is little effect on the speed of germination,
whereas with "priming," the target is to bring all seeds to a similar physiological
stage resulting in highly synchronized germination. In general, treatments
utilizing water or dilute solutions "advance" seeds, while treatments with
sufﬁciently concentrated osmotica to restrict water enough to prevent germination
"prime" seeds. Although in laboratory experiments certain pre-treatments
substantially improved both the speed and percentage germination, there are
inconsistent effects, particularly on seedling numbers in ﬁeld experiments
(Heydecker and Coolbear, 1977; Longden et al., 1979), which make it difﬁcult to
evaluate the usefulness or potential of such treatments. In the late 1980's, a new
method of priming was introduced termed solid matrix priming (SMP) (Taylor et
al., 1988). This method controls hydration through the metric potential in contrast
to traditional priming methods that employ osmotic potential. Rush (1991)
conﬁrmed that SMP promoted early emergence, suppressed pre-emergence
damping-off and produced a greater ﬁnal stand than osmoprimed treatments on
sugar beets. However, signiﬁcant suppression of post—emergence damping-off,
mainly caused by P. ultimum and A. cochlioides, was not achieved by using SMP
(Rush, 1992).

Pelleting tends to improve ﬂow through precision drills and also provides a
convenient carrier for insecticides, fungicides and some nutrients (Dunning, et
al., 1986). Until now, the principal component of the coating is a clay called
‘Filcoat’ that in the dry state has a few small pores. However, there is evidence

(Vanstallen, 1971; Thompson, and Woodwark, 1975; Verveka, 1983) that under

19

very wet conditions, such coatings decrease both the rate of germination and
ﬁnal germination percentage and that the less vigorous seeds are probably
affected most. There have been many comparisons of unpelleted and pelleted
seed in ﬁeld experiments, although, the results have not been consistent.
However, pelleting signiﬁcantly increased establishment in about ten percent of
the comparisons in England (Hibbert, et al.,1975).

Dunne et al. (1998), in order to satisfy both the public health and
environmental concerns, presented an alternative means for disease
suppression by using biological control. They found that the combined use of
Pseudomonas ﬂourescens, F113 and Stenotrophomonas maltophilia W81
protected sugar beet seedlings form Pythium-mediated damping-off as much as

when chemical pesticides when added in the pelleting medium.

Economic Impact

In the past ﬁve years, Michigan has produced approximately 13,000,000
Mg of sugar beets, making the crop one of the most important in the state.
Generally speaking, yield is the most important factor in determining net proﬁt
from sugar beet production. A proﬁtable yield needs to be preceded by a
satisfactory stand, however, it is estimated that 15.0 to 20.0% of ﬁelds need to be
replanted annually due to inadequate stands (Dr. R. Zielke, Director Research,
Michigan Sugar Company, Carrollton, Mich, personal communication). Poor
seedling vigor and problems with seedling survival to the four-leaf stage appear
to be major factors. It is estimated that loss of yield on replanted hectares is

approximately 300,000 Mg of beets. Replanting costs are about $12lha and the

20

loss in yield from replanting is estimated to be more than $36lMg. Thus, the total
cost of replanting is around $12 million annually to the Michigan sugar industry.
Much of this loss could be prevented by greater success in sugar beet

emergence, stand establishment and survival.

21

MATERIALS AND METHODS

Three experiments were conducted in 1998 and 1999. In the ﬁrst, results
of seven different laboratory tests were compared with the ﬁeld emergence of 20
seed lots. In the second, nine seed lots consisting of three different varieties and
three seed sizes were further compared in laboratory and ﬁeld tests in both 1998
and 1999. Finally, the effects of ﬁve different coating treatments on laboratory

and ﬁeld performance were evaluated on one seed lot.

Plant Material:

The seed lots used in the ﬁeld and laboratory experiments were obtained
from Michigan Sugar Co. (Caro, MI) and Monitor Sugar Co. (Bay City, MI).
However, the companies that produced the seed were American Crystal Sugar
Co., Betaseed (Shakoppee, MN) and Holly Hybrids (Sheridan, WY). All of the
seed was conditioned to remove a fraction of the outer portion (corky layer) of the
pericarp. The seed was then graded through sieve plates from sizes 2 (0.26 -
0.30-cm) through 5 (0.38 - 0.42-cm) in 0.04-cm increments. Since most of the
seed lots were commercially available, they were obtained pre-treated with a
commercial application of either Thiram or Apron® at the rate of 1.5 and 8 oz per
454-kg of seeds, respectively. Seed Systems Inc. (Gilroy, CA) applied all the
treatments in the seed enhancement experiment.

The seed lots were monogerm, a mendelian genetic trait, which produces

a single seed per fruit. The seed lots were of various ages depending on the

22

year of production. A smaller number of older seed lots with poor germination

(s 80%) were also selected.

Description of Laboratory Tests:

Laboratory tests for the three experiments in both years were performed in
a randomized complete block design. The procedures for each test were
identical for all the experiments, unless otherwise speciﬁed. Standard methods
for analysis of variance were used to analyze the laboratory data. All data were
analyzed using the SAS 7.0 Statistical Software package (SAS Institute Inc.
1998). The MIXED model procedure was used, allowing the handling of both

ﬁxed and random effects in a linear model, giving a continuous response.

1. Pleated Germination Test (PT)

Seeds were soaked in deionized water overnight (16 h) in 400-ml beakers.
Cheesecloth was attached to the top of each beaker with a rubber band.
Immediately after the soaking period the water was decanted and the container
reﬁlled and emptied ﬁve times for complete rinsing. The seed was then placed
on paper towels to dry for an hour.

Pleated germination paper (Anchor Paper Co., St. Paul, MN) was placed
into 12.7x17.8x12.7-cm plastic boxes containing 30 ml of deionized water.
Seeds were placed between the ﬂutes at the rate of four seeds per ﬂute, 100
seeds per lot, two lots per box. A paper clip was placed on the paper separating
the two seed lots within each box. Approximately 5 ml of additional water was

added by using a misting bottle to achieve uniform wetness of the paper. The

23

boxes were sealed when the seeds were in place. Four randomized replications
of each seed lot were 31
31genninated concurrently in boxes maintained at 230°C in a constant
temperature room under continuous ﬂuorescent light. Germination counts were
made at 5 (PT-5) and 10 d (PT-10) after planting.

Ungerminated seeds were opened with needle-nose pliers and judged to
either be live or dead, based on the embryo appearance. Abnormal seedlings

were not counted as germinated.

2. Cold Germination Test (CT)

Seeds were soaked overnight (16 h) in 400-ml beakers and rinsed as
described in the pleated paper germination test procedure, then planted in soil
from the Saginaw Valley Bean and Beet Farm near Saginaw, Michigan
(Misteguay soil complex having a silty clay texture) that had been passed
through a 0.64-cm sieve. One kg of soil was placed into plastic boxes measuring
18x33x9 cm, then leveled to a depth of approximately 1.9 cm. Then 50 seeds
were placed onto the soil using a counting board to assure equal spacing, and
another 1.0 kg of dry soil was placed over the seeds. Water was added from a
plastic bottle with a cap with small holes to allow even application without
disturbing the soil surface. Sufﬁcient water was added to bring the soil to 20%
moisture (2/3 of moisture at ﬁeld capacity).

Seed containers were randomized within germination chambers, with each
plastic box serving as one 50-seed replication. Two movable germination

chambers were utilized to represent two replications of each seed lot. The

24

chambers were placed in a constant temperature room maintained at

approximately 100°C for 4 d, then moved to a constant temperature room

maintained at 230°C for the duration of the test. Finally, three open plastic
containers were used to add deionized water to the top, middle and bottom part
of the chambers to assure high relative humidity.

Germination counts were made at 5 (CT-5) and 10 d (CT-10) of incubation
at 230°C. Seedlings were removed from each box after counting. Upon
completion of the ﬁnal count, the soil was air dried for a short time by passing it
again through a 0.64-cm sieve and allowing it to dry. After mixing, the soil was

again weighed into the boxes and the test repeated.

3. High Moisture Cold Test (C THM)
This test was similar to the CT, except that soil at 35% moisture was used

and germination counts were made at 3 and 6 d instead of 5 and 10 d.

4. Accelerated Aging Test (AA)

The initial seed moisture content was determined by weighing 5.0 g of
each seed lot (fresh weight) and drying in an oven at 105.0°C for 2.5 h; then the
seeds were reweighed (dry weight). If the seed moisture content was greater
than 14.0%, the seeds were dried to 10-14% moisture before the aging test
(AOSA).

The plastic accelerated aging boxes (11.0x11.0x3.5-cm) and the wire-
mesh trays (10.0x10.0x3.0 cm) were washed in a 15.0% sodium hypochlorite

solution (Clorox) and then dried. Forty ml of water were added to each. Then a

25

dry wire-mesh tray with approximately 17.0 g of sugar beet seeds in a uniform
layer was placed in each plastic box which was then sealed by placing a

Vaseline layer over the lid corners. The accelerated aging oven chamber was
set at 41 .0°C for 12 h before the test. Then plastic boxes were placed on a shelf
spaced approximately 2.5 cm apart and held at 410°C for 72 h with the door

continuously closed to prevent temperature ﬂuctuations. After the aging period,
the plastic boxes were removed and cooled to room temperature for an hour
before planting the seeds in pleated germination tests. Germination was

evaluated at 2 (AA-2) and 4 d (AA-4) after planting.

5. Saturated Accelerated Aging Test (AANaBr-2 and AANaBr-4)
This test was similar to the AA test, except that 60 ml of NaBr saturated

solution was added to each plastic box (11.0x11.0x3.5 cm) to maintain the
relative humidity at about 54.0%. All solutions were saturated at 41 .0°C (Jianhua,

and McDonald, 1996).

6. Conductivity Test (COND)
Prior to initial use, the conductivity meter was calibrated using a potassium

chloride solution. To calibrate the dip cell of the conductivity meter, 0.745 g of
pure analytical grade potassium chloride (dried at 150.0°C for 1 h and cooled in a
desiccator before weighing) was dissolved in 1 L of deionized water to make a
0.01M KCI solution, giving a 1 - 5 uS cm‘1 which was slightly higher than the

1.27tt8cm" (at 230°C) expected because of the low conductivity of the

26

deionized water. If the reading was incorrect, the calibration test was repeated

and the meter adjusted.

The initial seed moisture content was determined by weighing 5.0 g of
each seed lot (fresh weight) and drying in an oven at 105°C for 2.5 h; then the
seeds were reweighed (dry weight). All seed lots had a seed moisture content
of 11 - 14%.

Fifty ml of deionized water was placed in 50-ml ﬂasks which were covered
with aluminum foil to prevent dust contamination and equilibrated at 230°C for
approximately 24 h prior to placing the seeds in the water. A control ﬂask
containing only deionized water was included to monitor water quality.

Four subsamples of 75 treated seeds each were weighed and placed in
the 50-ml ﬂasks containing the deionized water (75 seeds per ﬂask). Each ﬂask
was gently swirled for ten seconds to ensure that all seeds were completely
immersed. Flasks containing water and seeds were recovered with aluminum foil
prior to being placed at 230°C for 24 h.

Immediately following the end of the 24-h soaking period, the conductivity

of the water in the ﬂasks was measured at 230°C. The ﬂasks (with seeds) were

swirled for 10 s, the foil removed and the conductivity 018 cm") determined by
immersing a pipette-type cell into the solution without ﬁltration. Direct contact of
the cell with the seeds was avoided and the dip cell was rinsed twice with
deionized water between samples. All hard seed (ﬂoating) observed during the

test were removed, surface dried, weighed, and the weight subtracted form the

27

initial weight of the 75-seed subsample. All the conductivity evaluations were

made inside the 230°C chamber to avoid temperature ﬂuctuations.

7. Sand Test (ST)

Seeds were soaked overnight (16 h) in 400-ml beakers and rinsed as
described in the pleated paper germination test procedure, then planted in blast
silica sand (Magnum Blast co.). First, 1.0 kg of sand was weighed in a plastic
bag and 40 ml of deionized water added to give four percent moisture. The sand
and water contained in the plastic bag were mixed for approximately one minute
to ensure even moisture distribution in the sand. The sand (1.0 kg) was placed
in18.0x33.0x9.0-cm plastic boxes and leveled to a depth of approximately 1.3
cm; then 50 seeds were placed on top of the sand using a counting board to
assure equal spacing. Another 1.0 kg of moist sand (4% moisture) was then
placed over the seeds and leveled. Finally, plastic wrap was placed onto the
boxes to prevent loss of moisture.

Seed lot containers were randomized within the germination chambers.
Each plastic box served as one 50-seed replication. Two movable germination
chambers were utilized to provide two replications of each seed lot and placed in
a constant temperature room maintained at 230°C for 10 d. Finally, 3 plastic
containers with deionized water were added to the top, middle and bottom part of
the chambers to assure maintenance of high relative humidity.

Germination counts were made at 5 (ST-5) and 10 d (ST-10) of incubation
at 230°C. Emerged seedlings were removed from each box after the ﬁrst count.

Upon completion of the ﬁnal count, the sand was discarded.

28

Experiment 1 (Seed Quality)

A. Seed Lots:

Twenty seed lots representing 12 varieties and seven different

years of production were used in 1998 (Table 1). Another 20 seed lots different

from those used in 1998 were tested in 1999. These consisted of eight varieties

representing six different production years (Table 2).

B. Laboratory Tests:

Six laboratory tests (PT, CT, AA, AANaBr, ST, COND) were

conducted on the 20 seed lots in 1998 as previously described. All tests except

AA, AANaBr, and ST were repeated in 1999. However, CTHM was conducted

 

 

 

only in 1999.
Table 1. Seed lots tested in Exp. 1 (Seed Quality) In 1998.
Entry Variety Source Lot No. Year Size

1 ACH—197 Michigan 6055324 93 3
2T ACH-308 Monitor 470346 93 3
3 ACH-319 Michigan 6102320 95 3
4 Beta 5931 Michigan 6105325 96 3
5 HM E 4 Michigan 635312 92 3
8 HM E 10 Michigan 6080321 93 3
91 uswzo Michigan uncertain 93 3
1o ACH-185 Monitor 219596 91 5
1 1 ACH-185 Monitor 328404 92 4
14 ACH-197 Monitor 320207 92 2
15 Beta 5931 Monitor 214206 92 2
16 HM E 4 Monitor 336420 92 4
17 HM E 4 Monitor 324211 92 2
161 USH-20 Monitor 82032 76 4
20 USH—23 Monitor 279307 66 3
21 ACH—185 Michigan 606310 96 3
52 HM E4 Michigan 931136 93 4
54 HM E4 Michigan 93514 93 3
56 ACH-319 Michigan 950427 95 2
57 ACH-319 Monitor 950427 95 3

1' Untreated Seed.

29

 

 

 

Table 2. Seed lots tested In Exp. 1 (Seed Quality) in 1999.

Entry Variety Source Lot No. Year Size
77 HM E10 Michigan 941025 94 4
78 ACH-319 Michigan 950514 95 2
79 ACH-319 Michigan 980027 98 3
80 HM E17 Michigan 980017 98 2
81 HM E17 Michigan 97005 97 3
82 HM E17 Michigan 980021 98 3
83 HM E17 Michigan 980019 98 3
84 ACH-555 Monitor 980444 98 4
85 ACH—848 Monitor 980285 98 3
88 ACH-555 Monitor 980444 98 2
87 HM E17 Monitor 970097 97 3
88 ACH-848 Monitor 980285 98 4
89 ACH-555 Monitor 980444 98 3
9O ACH-1353 MiIMo 980443 98 3
91 ACH-1353 MllMo 980443 98 2
92 ACH-1353 MilMo 980443 98 4
93 HM E17 Monitor 970095 97 4
94 HM E17 Michigan 980019 98 3
95 HM E17 Michigan 980015 98 2
98 HM E4 Michigan 931138 93 2

C. Field Study:

1998: Twenty seed lots were planted in three different locations.
An eight-row vacuum planter was used in location one and three with a space of
76 cm between rows. A four-row Almaco belt cone planter was used for location
two, with a space of 71 cm between rows. Planting depths were 1.3, 4.2 and 1.3
cm, respectively. Planting dates, locations and soil type are given in Table 3.
The seed spacing was 6.4 cm at all locations. Plot length was 6.1 m for all
locations. Single row plots were arranged in a randomized complete block
design with eight replications. Three ﬁeld emergence counts were made at each
location. The number of days after planting to ﬁnal emergence for each count

and respective dates are shown in Table 4.

30

Single linear correlation coefﬁcients (r) were calculated to show the
association among all laboratory tests and between single laboratory tests and

ﬁeld emergence. The linear regression model for r was y = a + bx + 6. However,

simple coefﬁcients of determination (r2) were used to illustrate the differences.
Multiple regression equations (R) were used to further explain the variability of
ﬁeld emergence using various laboratory tests in the same equation, rather than
single linear correlation coefﬁcients. Although the values were calculated as

multiple regression equations (R), multiple coefﬁcients of determination were

used (R2) to explain the differences in results. The equation used for the multiple

regression analysis was Y = (30 + (31x1 + (32X2 + 6... where Y was ﬁeld

emergence, X1 was the germination percentage in the pleated germination test
and X2 was the percent germination in the different vigor tests and 6 was the

error term that measured the deviation of a random variable from its mean.

 

 

Table 3. Farm, soil series and planting dates for ﬁeld studies of sugar
beet seed lots in 1998.
Location County Farm or Soil Planting
Farmer Series Date

1 Saginaw MSU 8&8 Misteguay 4/20
silty clay

2 Ingham MSU Campus Metea 4/24
sandy loam

3 Huron Maust Kilmanagh 4/22
loam

 

31

Table 4. Soil series, counting dates and days after planting for ﬁeld
studies of sugar beet seed lots in 1998.

 

 

Date

Location Soll Series 1't Count 2'" Count 3'‘1 Count
1 Misteguay 5/7 5/13 5/20
(Dap)T ‘I 7 23 30
2 Metea 5/8 5/12 5/19
(Dap) 13 19 28
3 Kilmanagh 5/4 5/14 5/21
(Dap) 12 22 29

 

T Dap= Days after planting.

1999: The twenty seed lots were planted in three different
locations using a four-row Almaco belt cone planter unit with 71-cm spacing
between rows. Planting depths were 3.2, 1.9 and 1.9 cm respectively. Planting
dates, locations and soil types are given in Table 5. The seed spacing was 6.4
cm and plot length was 6.1 m for all locations. Single row plots were arranged in

a randomized complete block design with eight replications.

Table 5. Farm, soil series and planting dates for ﬁeld studies of sugar
beet seed lots in 1999.

 

 

Location County Farm or Sell Planting

Farmer Series Date

1 Saginaw MSU 8&8 Misteguay 4/28

silty clay

2 Ingham MSU Campus Capac 4,14. 5,31
Botany loam

3 Ingham MSU Campus Metea 5/4
Crop 8. Soil sandy loam

 

1' Late sowing for Experiment Two.

32

Experiment 2 (Seed Sizes)
A. Seed lots:
Nine different seed lots were tested in both 1998 and 1999,
consisting of three varieties (ACH648, ACH503, ACH555) and three seed sizes
(2, 3, 4), all of which were produced in 1997. Entry number, variety, source, lot

number, year of production and size are given in Table 6.

 

 

Table 8. Description of nine seed lots In Exp. 2 (Seed Size) in 1998.
Entry Variety Source Lot No. Year Size
58 ACH-848 Michigan 970253 97 2
59 ACH—848 Michigan 970253 97 3
60 ACH-848 Michigan 970253 97 4
88 ACH-503 Monitor 970247 97 2
89 ACH-503 Monitor 970247 97 3
70 ACH-503 Monitor 970247 97 4
71 ACH-555 Monitor 970250 97 2
72 ACH—555 Monitor 970250 97 3
73 ACH-555 Monitor 970250 97 4

 

8. Laboratory Tests:

Seven laboratory tests (PT, CT, CTHM, ST, AA, AANaBr, COND,)
were conducted throughout both 1998 and 1999 on the nine seed lots as
previously described.

C. Field Study:

1998: The nine different seed lots were sown in three different

locations. An eight-row vacuum planter was used in locations one and three with

76 cm between rows. A four-row Almaco cone planter unit was used at location

33

two, with 71 cm between rows. Planting depths were 1.3, 4.2 and 2.5 cm
respectively. Planting dates, locations and soil type are given in Table 3. Plot
length was 6.1 m and seed spacing was 11.4 cm for all locations. Single row
plots were arranged in a randomized complete block design. A block consisted
of the nine experimental units (seed lots) and each block was replicated eight
times. Three ﬁeld emergence counts were made at each location. The dates
and number of days after planting for each count are shown in Table 4.

Simple coefﬁcients of determination (r2) were calculated for association
between laboratory and ﬁeld emergence results. Multiple coefﬁcient of
determination (R2) equations were used to establish the relationship between
laboratory test results and ﬁeld emergence for each planting date.

1999: The nine different seed lots were planted in two different
locations. However, in location two an early (4/14) vs. late (5/3) planting was
used to compare the differences due to date of planting. A four-row Almaco belt
cone planter unit was used for all locations, with 71 cm between rows. Planting
depths were 3.2, 1.9 and 1.9 cm, respectively. Planting dates, locations and soil
type are given in Table 5. A seed spacing of 10.2 cm and plot length of 6.1 m
was used. Single-row plots were arranged in a randomized complete block
design, with each block consisting of the nine experimental units (seed lots) and

each block replicated eight times within each location.

34

Experiment 3 (Seed Enhancement)

A. Seed Lots:

1998: One seed lot of variety HM E-17 produced in 1995 was
selected for this study. Five seed treatments were compared with the current
treatment, Celpril, as treatment number one. This gives a ﬁlm-coated treatment
of the fungicide Tetramethylthiuram disulﬁde, often known as Thiram®, along
with a dye to color the seed. The second treatment was a pelleted treatment
containing the fungicide, but no additional treatment (Plain Pellet). The third was
a pelleted seed that had been conditioned by a process referred to as priming
advanced treatment (PAT), a patented priming process to enhance speed of
emergence. During conditioning, PAT seed undergoes removal of germination
inhibitors as well as sophisticated control of moisture and temperature to promote
the very early stages of embryonic development. The fourth treatment consisted
of pelletized seed with the fungicide Tachigaren® added (TACH) to control the
seedling diseases caused by the soilborne Aphanomyces fungi. The ﬁfth
treatment utilized a pelleted seed combining the PAT process plus Tachigaren®
(PAT + TACH).

A second seed lot of HM E-17 produced in 1996 (as opposed to 1995)
was selected in 1999; otherwise, all the seed coating techniques used were the
same.

8. Laboratory Tests:

Two laboratory tests (PT, CT) were conducted on the ﬁve seed lots

in 1998 and 1999 as previously described.

35

C. Field Study:

1998: Field plots were planted at the Saginaw Valley Bean and
Beet Farm near Saginaw, Michigan on a Misteguay silty clay soil. All plots were
planted with a John Deere-71 plate planter unit mounted on a tool bar adapted
for the three-point hitch attachment to a tractor. Single row plots 12.2 m long
were arranged in a randomized complete block design with six replications but
were planted at 71 cm between rows. Seed was spaced at a distance of 10.2 cm
and a depth of 1.9 cm. An early (4/15) vs. late (5/15) planting was conducted to
compare the differences due to planting date. Emergence was measured seven
times for each planting date. A simple two-way analysis of variance (ANOVA)
was used to determine differences among treatments. However, correlation or
multiple regression analysis was not performed due to the lack of data points.

1999: Field plots were again planted at the Saginaw Valley Bean
and Beet Farm. However, three sites with different disease pressure were
Chosen within the farm. The area with low disease pressure had not had sugar
beets grown in the ﬁeld for more than 25 years. The medium ﬁeld location had a
rotation in which sugar beets were grown every three years. The high disease
pressure ﬁeld had a history of diseases and was one in which sugar beets had
been grown in both 1997 and 1998. Soil samples from the three sites were sent
to the Plant Disease Clinic at the University of Minnesota and assayed for the
presence of Aphanomyces sp. and other root rot pathogens. The disease index

for the three sites is provided in Table 7. A late planting date (5111) was chosen

36

to provide optimum conditions for disease development. Type of planter, plot

length, row space and seed spacing were the same as that used in 1998.

 

 

Table 7. Organism index values for the three sites for Exp. 3 (Seed
Enhancement) in 1999.
Site Organism lndex'I' Classiﬁcation
1 3 Low
2 28 Medium
3 94 High

 

T Values fall between 0 and 100. A value of 0 means that no disease was
detected. A value of 100 means that roots of all plants were severely
rotted or that all seedlings died in the greenhouse bioassay.
Planting depth was increased to 2.5 cm to attain a more uniform plant stand
because of more optimum moisture for germination. A single block consisted of
the ﬁve treatments repeated four times. Emergence was measured four times at

9, 14, 17 and 21 d after planting for all sites. A simple two-way analysis of

variance was used to determine the differences between treatments.

37

RESULTS AND DISCUSSION

I. Laboratory Tests

A. Means and Coefﬁcients of Variance

The highest mean emergence of 92.5% occurred for the 10-d pleated
germination test for the Exp. 1 (Seed Quality) in 1998 (Table 8). On the other
hand, the lowest mean germination (13.7%) occurred at the 2-d accelerated
aging test for the same experiment. The difference between the 10d pleated
germination (PT-10) and the 10-d cold test (CT-10) results was 13.1% for Exp. 1
in 1998. A difference of 13.0% germination occurred between means of the 10-d
sand test (ST-10) and PT-10. A similar difference of 15.4% occurred between
results of the 4-d accelerated aging test and the sodium bromide (AANaBr—4)
test, however, a larger germination difference of 56.0% occurred between the 2-d
standard accelerated aging (AA-2) and PT-10 tests. In Exp. 1 in 1999 the PT-10
again produced the highest mean emergence at 94.0% (Table 9). However, the
lowest mean emergence of 58.3% occurred for the 3-d cold high moisture test
(CHM-3). For the same experiment, a mean difference of only 2.0% occurred
between germination results for the PT-10 and CT-10. However, there was a
14.1% germination difference between the PT—10 and 6-d high moisture cold
germination test (CTHM-6). Similar differences occurred in Exp. 2 (Seed Size),
however, the largest difference of 78.6% occurred between PT-10 and AA-2
(Table 10). The highest mean emergence of 94.0% also occurred at the PT—10
and the lowest mean emergence occurred at the 2—d count of the accelerated

aging test. In Exp. 3 (Seed Enhancement) in 1998 the highest mean of 98.6%

38

for PT-10 was shared between the advanced primed seed (PAT) and the plain
pelleted seed (Plain), however, Tachigaren-treated (TACH) seed germinated only
67.0% (Table 11). All 10-d cold germination test means in Exp. 3 were above
90.0%, including Celpril treated seed at 99.0%, but were only 92.0% for PAT.
However, the highest PT-10 mean germination in 1999 was from plain pelleted
seed at 96.3%, and the lowest for PAT+TACH at 80.5%. In the CT-10 the Plain

treatment produced the highest mean at 97.5% and the lowest was PAT + TACH

 

 

at 79.5%.

Table 8. Mean, coefﬁcient of variance and range of laboratory test
results averaged over all seed lots tested, Exp. 1 (Seed
Quality), 1998.

Lab Tests Mean CV RangeT

(% germinated)

PT—5 87.9 18.8 17 - 100

PT-10 92.5 9.73 59 - 100

CT-5 78.7 28.4 0 - 100

CT-10 79.4 25.5 10 - 100

ST-5 66.7 34.3 o - 100

ST-10 79.5 22.7 10 - 100

AA-2 13.7 128.0 0 - 73

M4 36.5 54.8 1 - 75

AANaBr-2 26.6 75.2 o - 80

AANaBr-4 77.1 28.2 13 - 100

COND: 480.1 16.9 299.9 - 620.5

 

1' The range of values is for all the replications.
1 Values for the tests are expressed as % of seed germinated, except
COND that is in (18 cm "9 ".

39

Table 9. Mean, coefﬁcient of variance and range of laboratory test
results averaged over all seed lots tested, Exp. 1 (Seed
Quality), 1999.

 

 

Lab Tests Mean CV RangeT
(% germinated)

PT-5 93.2 4.6 60 - 100
PT-10 94.0 4.6 80 - 100
CT-5 90.9 7.6 62 - 100
CT-10 92.0 7.3 64 - 100
CTHM-3 58.3 41.1 0 - 92
CTHM-6 79.9 17.9 36 - 96
COND: 531.7 19.0 391.5 - 840.0

 

1' The range of values is from four replications.
1: Values for the tests are expressed as % of seed germinated, except
COND that is in 118 cm “9 ".

40

Table 10. Mean, coefficient of variance and range of laboratory test
results averaged over all seed lots tested, Exp. 2 (Seed Size).

 

 

Lab Tests Size Mean CV RangeT
(%jerminated)

PT-S - 93.2 4.6 80 - 100
PT-10 .- 94.0 4.6 80 - 100
CT-5 - 69.9 5.1 62 - 96
CT-10 - 91.5 4.7 84 - 100
CTHM-3 - 49.1 74.6 10 - 74
CTHM-8 - 76.9 23.2 66 - 96
ST-5§ 2 55.6 21.6 30 - 70

3 70.7 14.2 56 - 66

4 71.0 46.7 52 - 62
ST—10§ 2 76.6 12.1 66 - 96

3 66.7 6.0 76 - 96

4 65.7 7.4 72 - 96
AA-2 -- 0.61 138.8 0 - 5
M4 -- 15.4 37.4 3 - 29
AANaBr—2 -- 7.2 70.5 1 - 22
AANaBr-4 - 77.6 13.0 36 - 92
corvoiv§ 2 579.4 16.7 424.5 - 713.0

3 488.2 13.7 361.2 - 570.6

4 455.2 10.9 379.3 - 529.2

 

1’ The range of values is for all the replications.

:1: Values for the tests are expressed as % of seed germinated, except
COND that is in 1.18 cm "9 “.

§ Only tests where the variable size was signiﬁcant P s 0.05 in the
ANOVA.

41

Table 11. Mean, coefﬁcient of variance and range of seed treatment test
results, Exp. 3 (Seed Enhancement).

 

 

 

 

 

 

1996 1999
Lab Tests Mean CV RangeT Mean CV Range
% germination of seed tested

PT-5
CBIPI'II 66.0 6.2 66.0 - 94.0 67.6 4.4 64.0 - 3.0
PAT 96.6 3.6 96.0 -100.0 64.0 7.5 76.0 - 69.0
TACH 61.0 13.6 56.0 - 66.0 79.3 4.2 75.0 - 63.0
PAT+TACH 63.6 21.6 76.0 - 96.0 77.5 3.9 73.0 - 79.0
Plain 96.0 4.6 96.0 - 100.0 95.5 1.6 94.0 - 96.0

PT—10
COIpI'iI 97.6 5.2 94.0 - 100.0 91.2 3.1 66.0 - 95.0
PAT 96.6 3.6 96.0 - 100.0 66.3 6.0 79.0 - 90.0
TACH 67.0 12.4 62.0 - 72.0 63.5 4.4 60.0 - 66.0
PAT‘I’TACH 69.6 22.4 76.0 - 96.0 60.5 4.6 76.0 - 64.0
Plain 96.6 3.6 96.0 - 100.0 96.3 1.3 95.0 - 96.0

CT-5
COIpl‘II 97.0 3.9 92.0 - 100.0 95.0 3.6 92.0 - 100.0
PAT 91.0 5.2 64.0 - 94.0 66.0 9.3 76.0 - 96.0
TACH 93.0 1.2 92.0 - 94.0 93.5 4.7 90.0 - 100.0
PAT'I'TACH 97.0 1.2 96.0 - 96.0 76.0 7.5 72.0 - 64.0
Plain 95.0 2.7 92.0 - 96.0 97.0 3.6 92.0 - 100.0

CT-‘Io
COIpI‘II 99.0 2.0 96.0 - 100.0 95.0 3.6 92.0 - 100.0
PAT 92.0 5.9 64.0 - 96.0 66.5 9.3 76.0 - 96.0
TACH 94.0 1.7 92.0 - 96.0 95.0 4.0 92.0 - 100.0
PAT'I'TACH 97.5 1.0 96.0 - 96.0 79.5 6.6 74.0 - 64.0
Plain 95.5 2.0 94.0 - 96.0 97.5 3.9 92.0 - 100.0

 

1' The range of values is for all the replications.

42

The wide range between the pleated and cold test germination in Exp. 1 in
1998 showed the variation of seed quality. This is largely due to the impact of
seed lots 18 and 10, which represented the lowest quality (Table 12). Although
this may have been expected due to the age of these particular entries, the
variation in seed quality for Exp. 1 in 1998 was also reﬂected by the larger
coefﬁcient of variation when compared with the other experiments (Table 8 - 11).
Although viability tests usually do not detect vigor differences, they can be useful
in determining some differences when such large variation in seed quality exists.

Most seed lots in Exp. 1 in 1999 and the other two experiments were of
acceptable market quality, deﬁned by the sugar beet industry as 92.0% or higher
in the pleated germination test. Most lots in these studies would have been
acceptable except seed lots 85, 91 and 96, which did not meet the criteria in our
pleated germination test (Table 13).

Application of external stress to the seed holds promise as an additional
means of measuring seed quality. In these experiments, three such tests were
evaluated. Generally, there was a lower germination for the vigor tests than for
the pleated test. Ten-day pleated germination averaged 92.5% across 20 entries
in Exp. 1 in 1998, but none of the vigor tests averaged above 80.0% (Table 12).
The sand emergence, accelerated aging over sodium bromide and cold test all
had similar averages (77.1 - 79.6%). Accelerated aging over water had much

lower values, with an average of 36.5%. This test was not particularly

43

 

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46

useful because of excessive mold development on some entries during
incubation at 410°C. Similar results were found in the rest of the experiments.
However, cold test results across seed lots in Exp. 1 (1999), 2 and 3
(1998 - 1999) were more than 100% higher than that of Exp. 1 in 1998
(Table 12 - 15). These higher results may have been due to temperature
ﬂuctuations (lower than 9.0°C) in the cold room and lack of proper maintenance
of the soil moisture. Both factors have a direct effect on soilborne plant
pathogens, which is thought to be the primary factor inﬂuencing the cold test
germination (Woltz, et. al. 1998). This observation is also supported by the lower
mean germination in the high moisture cold test for the same experiment
(Table 13 and 14).

The conductivity test produced the lowest average conductance values in
Exp. 1 in 1998 (480.1 uS cm‘1 9“, Table 12). This was unexpected because
Exp. 1 had the two lowest quality seed lots (entries 10 and 18). Low vigor seeds
generally possess poor membrane structure and leaky cells, resulting in greater
loss of electrolytes such as amino acids, inorganic ions and organic acids from
seeds. These electrolytes increase conductivity in the soak water; therefore, a
low vigor seed lot should posses the highest conductivity. However, this high
conductance typically produced by low vigor seed lots was not observed
(Table 12). Although the conductivity test on sugar beets has not been a good
indicator of seed quality in previous investigations (Longden and Johnson, 1974

and Kraak et al., 1984), a possible explanation for poor quality seed lots

47

producing a low conductance might have been due to a masking effect of seed
size on conductance. ln conductivity measurements of the soak water in which a
bulk sample (75 seeds) had been steeped, seed size had a direct inﬂuence on
the conductance. To illustrate the point, the size of this entry (# 18) was four
(Table 1), the second largest of the four sugar beet sizes. Large seeds have a
smaller surface area per unit weight, resulting in a lower diffusion rate than from
small seed (Tao, 1978 and Bekendam, et al 1987). This observation was also
conﬁrmed in Exp. 2, in which smaller seed within the same variety had the
highest conductivity of the three varieties tested (Figure 1). Otherwise there is
large inconsistency in both conductivity and germination test results. However,
another possibility for these results was the potential inﬂuence of seed treatment
in the conductance of the water. Following the rationale explained above, seed
from smaller size posses the largest amount of seed treatment per unit weight,
thus perhaps inﬂuencing conductance. This emphasizes the need for

standardization of vigor test procedures.

8. Simple Coefﬁcients of Determination

Simple coefﬁcients of determination were used to establish the
relationship between ﬁeld emergence and laboratory test results. Signiﬁcant
coefﬁcients of determination of r2 in excess of 0.500 occurred among results in
Exp.1 and 2 (Tables 16, 17 and 18). A relationship of r2 = 0.787 occurred

between the 5- and 10-d germination periods for the sand emergence, and the

48

2- and 4-d counts of the accelerating aging test over water and NaBr in Exp. 1 in
1998 (Table 16). However, there was a better relationship within the 5- and 10-d
counts for the pleated test (r2 = 0.890) and a larger coefﬁcient of determination
between 5- and 10-d counts of the cold test (r2 = 0.990). Similar results were
found in 1999, where relationships between the pleated germination and cold test
were r2 = 0.980 and 0.966, respectively (Table 17). However, the high moisture
old test had a 3- and 6—d coefﬁcient of determination of just r2 = 0.691. In Exp. 2

the relationships between pleated germination and cold test results were also

high (r2 = 0.853 and r2 = 0.875). Smaller coefﬁcients (r2 < 0.780) occurred

 

  
 
 
  

 

 

 

 

 

 

Conductivity Test
700
a Lsom=533

600 - - Size 2
.5‘ Size 3
-:-°’ 500 .. - Size 4
E
O
‘3
v 400 -
.2‘
.E
‘9 300 -
'O
C
O
0 200 .

100 —

o _
ACH648 ACH503 ACH555
Variety

Figure 1. The effect of seed size on conductance for the three varieties
tested on Exp. 2.

49

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52

among the other test results (Table 18), however, coefﬁcients for the high
moisture cold test and accelerated aging test over water were not signiﬁcant.
These data suggest that a 5-d count may be sufﬁcient for the pleated germination
and cold tests, but the longer period is needed for the other tests.

There was not a close coefﬁcient of determination among results of the
various tests for the two experiments (r2 < 0.830, Table 16 - 19). However, the
highest coefﬁcient was between the pleated germination and cold test (r2 =

0.825) in Exp. 1 in 1998. A similar coefﬁcient (r2 = 0.804) occurred between

results of the pleated germination and accelerated aging over NaBr for the same

experiment. Also, a relationship of r2 5 0.737 occurred between results of the
sand test and the pleated test. In Exp. 1 in 1999 the coefﬁcient of determination

between the pleated germination and cold test results was lower than expected

(r2 = 0.750), but was the highest among tests for that year (Table 17).
Coefﬁcients between the pleated germination and cold test results in Exp. 2 were
not signiﬁcantly different. The coefﬁcient of determination between sand test and
accelerated aging results over sodium bromide was of 0.780 for the same
experiment. Results of Exp. 1 in both years support the use of the cold test as
an indicator of viability, conﬁrming observations of Akeson and Widner (1980)
and Lovato and Cagalli (1992).

Conductivity test results were poorly correlated with other test results in all

experiments (r2 5 0.254). Sugar beet seeds consist of thick outer pericarp layers
that disable the easy flow of the leakage of organic substances from the

endosperm to the epidermis. The lack of signiﬁcant coefﬁcients of determination

53

between the conductivity test and other test results conﬁrmed the research of

Kraak, et al. (1984) and Bekendam, et al (1987).

ll. Relationship Between Laboratory Test and Field Emergence
A. §imgle Coefﬁcients of Determination

Simple linear coefﬁcients of determination were computed among all
laboratory results and ﬁeld emergence for Exp. 1 and 2, but not for Exp. 3
because of inadequate data points collected. Many signiﬁcant coefﬁcients of
determination greater than 0.500 occurred in Exp. 1 in 1998 (Table 19), but only
a few for the same experiment in 1999 and Exp. 2 (Table 20, 21 and 22). This is
consistent with observations from studies by Burris (1976) and Durrant et al.
(1984). They found when seed lots with poor viability were included, coefﬁcients
of determination between ﬁeld emergence and laboratory results were higher

than when only seed of acceptable market quality was used.

The 5-d cold test had the highest coefﬁcient of determination (r2 = 0.917)
for the ﬁnal count at the Metea location in Exp. 1, 1998 (Table 19). In all three
locations the cold test and pleated germination test had the higher coefﬁcients.

In contrast, the conductivity test and the accelerated aging test over water had
lower coefﬁcients (r2 s 0.467). The highest signiﬁcant coefﬁcient with ﬁeld
emergence of r2 = 0.588 occurred for the 10-d pleated test in the same

experiment in 1999 (Table 20). Although lower than r2 = 0.500, the cold

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58

test produced the second best coefﬁcient for this experiment. The high moisture

cold test performed no better than the standard cold test, for which the highest

coefﬁcient (r2 = 0.394) occurred at the Metea location. The conductivity test did
not produce signiﬁcant coefﬁcients with ﬁeld emergence at any of the three
locations and no signiﬁcant coefﬁcients for any test at the Capac location.
Coefﬁcients of determination at all three locations for Exp. 2 in 1998 were
low and not signiﬁcant (Table 21), perhaps due to the small sample size (n=9),
smaller vigor differences and generally higher quality seed than that used in Exp.
1 in 1998. Although not signiﬁcant, the cold test results had the highest
coefﬁcients with ﬁeld emergence at all locations for Exp. 2 in 1998. Few
signiﬁcant coefﬁcients occurred for Exp. 2 in 1999 (Table 22). However, there

was a better coefﬁcient between the 10—d cold test and ﬁeld emergence at the

early sowing compared to the late sowing (r2 = 0.857 vs. r2 = 0.654) for the
same number of days after planting. Surprisingly, the conductivity test had
slightly lower signiﬁcant coefﬁcients of determination with ﬁeld emergence than
the cold test for the early planting, however, at the late planting, none of the
conductivity coefﬁcients were signiﬁcant. These results could be due to the
favorable soil conditions for the early planting.

Comparisons from all experiments showed that the cold test had the
highest or second highest coefﬁcient of determination with ﬁeld emergence.
Since the cold test measures emergence under artiﬁcially induced cold soil
conditions it would be expected to correlate well with performance under ﬁeld

stress conditions, especially at the early planting of Exp. 2 in 1999 (Akeson and

59

Widner, 1980; Kraak et al., 1984). The better soil environment simulates the
conditions used to demonstrate the vigor response in the laboratory, resulting in
better coefﬁcients between cold test vigor and ﬁeld emergence.

While coefﬁcients of determination between pleated germination test
results and ﬁeld performance were highly signiﬁcant in Exp. 1 in 1998, they were
usually lower than those for all the experiments. These results agree with those
of several other authors who have concluded that the standard germination test
is reliable for predicting plant establishment of sugar beets in the ﬁeld (Kraak et
al., 1984; Durrant, Brown and Bould, 1985).

The coefﬁcients of determination between ﬁeld emergence and sand test
results were the third highest for Exp.1 in 1998 (Table 19), however, such
coefﬁcients were not achieved in any subsequent year or experiment. This is
contrary to results obtained by Akeson and Widner (1980) in which sand test
results for sugar beets were highly correlated with ﬁeld emergence (r2 = 0.792 -
r2 = 0.960).

Aging, which is considered to be a major cause of reduced vigor in seeds
(Perry, 1972), also failed to result in high correlation between laboratory tests
and ﬁeld emergence (Durrant et al. 1984; Kraak, and Vos, 1987). However, the
physiological changes during the accelerated aging test may be different from
those produced by normal aging processes. The low correlation with ﬁeld
emergence is in striking contrast with results cited earlier for large-seeded crops
such as corn and soybean in which the accelerated aging test over water is an

important seed vigor test. However, its value for small-seeded crops has been

60

limited because moisture uptake is too rapid, resulting in rapid seed deterioration
for some species. Therefore, the accelerated aging over NaBr which only
provided a relative humidity of 55.0% vs. ~ 100.0% over water showed signiﬁcant
coefﬁcients of determination only in Exp. 1 in 1999.

Measurement of the exudation of inorganic and organic electrolytes into
water provides a rapid method for testing viability (Takayanagi and Murakami,
1968), however, for small-seed crops this measurement may not be useful
(Longden, and Johnson, 1974; Kraak, and Vos, 1987). With the exception of the
early planting in Exp. 2 in 1999, the conductivity test was poorly correlated with
ﬁeld emergence. Although this test is very convenient and can be completed in
one day, its use in predicting ﬁeld establishment does not merit further attention.

No single laboratory test consistently had the highest simple linear
coefﬁcient of determination with ﬁeld emergence for all stand counts over all
locations. This is consistent with the opinion of many scientists that a single
laboratory test simply cannot correlate well with ﬁeld emergence over the entire
range of possible planting conditions. Although these data conﬁrm this
hypothesis, they also show correlations between ﬁeld emergence and different

laboratory test results.

8. §tepwise Multiple Regression Analysis

Laboratory and ﬁeld emergence results were analyzed using a multiple

stepwise regression technique. Results in Exp. 1 in 1998 (Table 23) show very

good multiple coefﬁcients of determination (R2) between 0.814 and 0.879.

61

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The 5-d cold test was the signiﬁcant variable in two of the three locations in Exp.
1. However, the 10-d pleated test alone accounted for 87.9% of the total
variability for the Kilmanagh location.

The high moisture cold test appeared in three regression equations for

Exp. 1 in 1999 (Table 24), with R2 values ranging from 0.211 (not signiﬁcant at
P5005) for the Capac location to 0.611 (signiﬁcant at P5005) for Misteguay.
Although the high moisture cold test did not by itself have a high simple linear
coefﬁcient of determination with ﬁeld emergence, along with the 5-d pleated
germination or 5—d cold test, it made a signiﬁcant contribution to the multiple
coefﬁcients of determination equations, explaining about 11.0% of the variation

for this experiment.

The highest and the lowest R2 values of 0.980 and 0.486 occurred for the
Kilmanagh and Metea locations, respectively, for Exp. 2 in 1998 (Table 25).
Again, the cold test appeared in the multiple coefficient of determination equation
for two of the three locations, and the conductivity test made a signiﬁcant
contribution in two of the three equations. However, the conductivity test was not
by itself signiﬁcantly correlated with ﬁeld emergence at any location.

The coefﬁcient of multiple determination for Exp. 2 in 1999 (Table 26) was
lower than that of the same location for 1998 (Misteguay). However, the 2-d
accelerated aging over sodium bromide test accounted for more than twice the
variability in 1999 than in 1998 for the same experiment. Furthermore, the 10-d
cold test appeared as an independent variable for two of the three locations.

Early planting had a higher coefﬁcient of determination than late planting at 0.873

65

and 0.645, respectively, for the Capac location in the same experiment. Cooler

soil and better soil conditions were factors that contributed to a higher R2 value,
conﬁrming observations by Kraak, et al. (1984) and Payne and Williams (1990).
High soil temperature and moisture during seedling development favor growth of
Aphanomyces cochlioides and thus the incidence of infection. This is specially
true for late plantings with warmer temperatures at which may lead to partial or
complete stand establishment failure in some years. Damping-off caused by
Pythium spp. is less frequent in the ﬁeld, but may be under-reported because
infected seedlings die before or soon after emergence.

Since the cold and pleated germination tests appeared in most of the
stepwise multiple coefﬁcients of determination, equations with these two

variables were computed for all locations for both experiments in both years.

However, Table 27 and 28 show that the R2 values were not signiﬁcant, and no
better than those for the stepwise multiple regression equations when all other
tests were included.

The use of a combination of tests to predict ﬁeld emergence of sugar beet
has been suggested by other investigators (Longden, and Johnson 1974; Kraak,

et al. 1984; Yaklich and Kulik 1979; Durrant, et al. 1984; Lovato and Cagalli

1992). Likewise, in soybeans, Yaklich (1979) used the best R2 values from all
possible multiple regression equations to evaluate the usefulness of similar vigor

tests. By using a number of laboratory tests to measure several different aspects

of vigor, test combinations having high R2 values have been found that will

predict ﬁeld emergence results under similar seedbed conditions. However,

vigor test results reﬂect the conditions of the individual test and may not explain

all the processes and reactions occurring at the ﬁeld level.

III. Inﬂuence of seed size on germination and field emergence (Exp. 2)

A. Laboratom Tests:

In most comparisons, seed size was not signiﬁcantly associated with
pleated seed germination (Table 29). The cold test did not produce signiﬁcant
differences among seed sizes. Three-day high moisture cold test results on seed
size two was signiﬁcantly different than on those of size four for the variety
ACH55. Two of the three varieties showed a signiﬁcant difference in the sand
test performance between seed sizes two and four. Few differences also
occurred among seed sizes in the accelerated aging test, however, little
consistency occurred among results of accelerated aging tests over water vs.
sodium bromide. Signiﬁcant differences in conductivity test results between the
smallest and largest seed sizes (two and four) occurred for the three varieties
tested. Surprisingly, the smallest seed size produced the highest conductance
and vice versa, however, an explanation for the masking effect of seed size on

the conductance of water was previously explained in section IA.

B. Field Emergence:
Contrary to ﬁndings by Lexander (1981) and Akeson (1981), seed size did

not have a signiﬁcant overall inﬂuence on ﬁeld emergence in 1998 (Table 30).

The 12-d Kilmanagh and Misteguay 23-d counts for the ACH503 variety were the

67

only comparisons that produced signiﬁcant emergence differences between size
two and four for the same year. In 1999 the early planting produced no
signiﬁcant differences in emergence due to seed size, which is consistent with
1998 ﬁndings (Table 31). However, in the late planting most of the comparisons
produced signiﬁcant differences in emergence due to seed size. Although no
relative ranking was made, signiﬁcant differences between seed size two and
four occurred in almost all of the comparisons.

Many growers believe that larger seeds have better emergence potential
than smaller ones, however, my research did not support this belief. Although
larger seeds had significantly higher emergence at the late planting in 1999, this
"grower belief" can not be consistently conﬁrmed because such late planting
dates are not feasible. Akeson (1981) also reported no differences in ﬁeld
performance for seed size of 3.6 - 4.0-mm vs. 3.2 - 3.6-mm. Lodgen (1986)
indicated that large seeds did not necessarily germinate better than small ones

since large seeds could be a result of increased pericarp volume alone.

IV. Inﬂuence of Seed Treatment on Field Emergence (Exp. 3)

All seed treatments produced higher emergence than the standard Celpril
treatment (ﬁlm coating with Thiram) for all counts at the early planting (4/15) in
1998. However, the priming advanced treatment (PAT) resulted in earlier
emergence than any other treatment. At the 11-d count, PAT-treated seed
emerged 97.7%, more than the standard treatment with Celpril (Figure 2). Celpril

treated seed always had the lowest emergence for this planting date. Although

68

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71

the relative ranking among the other treatments was not consistent, all the seed
treatments induced similar emergence to that of PAT treated seed at the later
counts. At the last count (44—d) the PAT and Plain Pelleted seed emerged
60.0%, which was approximately 10.0% higher than Celpril treated seed.
However, none of the seed treatments were able to meet the goal of the so-
called "crop success" of 70.0%.

In the late planting (5/15) in 1998, overall trends in stand establishment
were similar to those in the early planting, however, the stands for all seed
treatments were signiﬁcantly lower. Again, PAT treated seed emerged earlier
than that of other treatments. Nineteen days after planting, 10.8% of seedlings
from PAT treated seed had emerged, compared with only 2.6% of those from the
Celpril treatment (Figure 2). However, the other three seed treatments induced
similar emergence to that of PAT treated seed at later counts. Furthermore, the
difference among treatments was not signiﬁcant at the 38-d, 42-d and 45-d
counts.

Priming has been shown to increase the earliness and uniformity of sugar
beet seedling emergence (Durrant et al. 1983, Longden et al. 1979, Osbum, and
Schroth, 1988), resulting in a lower incidence of seedling loss due to damping-off
pathogens such as Pythium ultimum Trow (Harman and Taylor, 1988; Osbum,
and Schroth, 1988 and 1989; and Rush 1991 and 1992). Pythium spp. is a
soilborne pathogen that can infect the seed very quickly after planting, inhibiting
germination and resulting in poor stands from both pre-emergence and post-

emergence damping-off. However, the pre-emergence phase is more common.

72

 

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Protection against Pythium ultimum has been attributed to escape, reduction in
seed exudates and a decrease in indigenous bacteria on primed seed (Leach,
1947; Leach and Smith, 1945; Osburn and Schroth, 1989). Although seed
priming can reduce loss to seedling infection by Pythium ultimum, seedling
disease caused by Aphanomyces cochlioides is not affected (Rush, 1992). A.
cochlioides is a warm-temperature pathogen which typically infects the
hypocotyls of sugar beet seedlings after emergence and is dependent on almost
saturated soil for zoospore movement and infection (Buchholtz, 1944a and
1944b, McKeen, 1949; Papavizas and Ayers, 1974). However, in these studies,
Celpril coated seed was not as effective as PAT against soilborne pathogens,
especially in the late planting. Thiram is thought to be more effective against
seedborne pathogens (like Phoma betae) rather than soilborne pathogens
(Durrant, et al., 1988, Payne, and Williams, 1990). However, there is a possibility
that steeping seed in Thiram could exert some control on soilborne pathogens
from either a fungicidal effect (Maude, 1983) or as a result of increased seedling
vigor, reducing the period during which seedlings are susceptible to infection
(Durrant, et al., 1988). However, earlier studies showed that when Thiram and
hymexazol are present in a seed pellet, protection against Phoma betae, Phoma
spp. and A. cochlioides might be achieved, depending on the relative amount of
soilborne pathogens present (Payne, and Williams, 1990).

Although similar stand establishment levels occurred at both planting
dates, the overall mean emergence was much lower at the late planting. For

example, plain pelleted seed had the highest emergence at 28.8% for the late

74

planting (31-d count) compared to 59.9% (28-d count) for the early planting.
Colder temperatures during the ﬁrst planting and warmer temperatures at the late
planting, along with 36 mm of rain in the week before late planting and poorly
drained soil conditions all contributed signiﬁcantly to the lower stand counts for all
seed treatments at the late sowing. A. cochlioides and Pythium spp. alone or in
combination are frequently cited as signiﬁcant causes of seedling loss in different
countries (Dunning and Heijbroek, 1981, Papavizas and Ayres, 1974; Yanaguchi,
1977). However, Pythium spp. which attacks younger seedlings appears only
brieﬂy and do not cause major crop losses (Payne, and Williams, 1990). In
contrast, the warm-temperature pathogen A. cochlioides, can cause detrimental
effects by infecting the tap root and ﬁbrous root system of the developing crop
under high temperature and wet soil conditions (Papavizas and Ayres, 1974).

In a survey of fungi causing seedling diseases conducted in Europe in the
early 1980's, A. cochlioides and Pythium spp. were found to occur in 39.0% and
31.0%, respectively, of 341 sugar beet ﬁelds surveyed (Payne, et al., 1994).
However, the frequency of A. cochlioides-infested soils varied widely in the
different sugar beet growing areas. To mimic this variation in 1999 our research
mnsisted of three sites with different indices of Aphanomyces spp.. A soil
bioassay showed the index of 3, 28, and 94.0% for Sites 1, 2, and 3, respectively
(Table 7).

In Site 1 where the organism index was low, no signiﬁcant differences
were found between seed treatments for the ﬁrst three emergence counts

(Figure 3). However, at the last count (21-d), signiﬁcant differences in

75

emergence occurred between Plain pelleted seed and the combination of primed
advance treatment with the fungicide Tachigaren (PAT+TACH). The highest
(78.8%) and the lowest (64.5%) emergence occurred for Plain pellet and
PAT+TACH treated seed respectively, throughout the four counts. The overall
emergence for all seed treatments on Site 1 was high. This is not surprising
since no beets had been grown in this ﬁeld during the past 25 years, resulting in
minimal disease inoculum potential. However, in Site 2, sugar beets had been
grown in a three-year rotation with other crops, therefore the organism index was
medium and clear emergence differences and lower mean emergence occurred.
At the 21—d count the highest ﬁeld emergence levels of 63.5 and 62.5% occurred
for the standard ﬁlm coating treatment Celpril and the Plain pelleted, respectively
(Figure 3). Contrary to the ﬁndings in Sites 1 and 3, the highest emergence was
with PAT+TACH treated seed (38.5%). There is a possibility that coating with
Thiram (the fungicide in the Celpril treated seed) could exert control on soilborne
pathogens, either from a fungicidal effect or as a result of enhancing seed
germination and reducing the period during which seedlings are susceptible to
attack. However, when Celpril was compared in a high organism index
environment like that of Site 3, the incidence of seedling mortality from infection
by Aphanomyces spp. was as low as that for Plain pellet treated seed (Figure 3).
At the 21 —d count 14.8% emergence occurred for both treatments, indicating that
Thiram alone does not perform well under severe disease conditions. However,
when combined with a treatment that will enhance germination with a fungicide

(Tachigaren), like PAT+TACH treatment, a sugar beet stand can be tripled under

76

Emergence (%) Emergence (%)

Emergence (%)

Field Emergence for Experiment Three - 1999

 

100

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ab

 

Site Three (High Disease Index)

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PAT+TACH
- Plain

 

 

 

Figure 3. Effect of seed treatments on seedling emergence from soils
infested with different level of Aphanomyces spp.

77

conditions with severe pathogen levels (41.0%). Thus, at the 9-d count all the
treatments had a signiﬁcantly higher emergence than those at Site 2 for the
same count. However, the mean emergence of all seed treatments was
signiﬁcantly lower at 21-d in Site 3 compared with Site 2 for the same time.
Higher incidence of Aphanomyces spp., wet soil, high temperatures and cut
worm damage all contributed to the gradual stand establishment loss in the

Site 3.

78

SUMMARY

Comparisons of seed quality/vigor test and ﬁeld emergence results were
made in 1998 and 1999 in three different experiments. Experiment One utilized
seed lots representing a wide range of seed quality, from different production
years and lengths of storage. Seed lots used in Exp. 2 were of high quality and
represented three varieties with three different seed sizes. Experiment Three
consisted of a commercially grown seed lot enhanced with the following ﬁve seed
treatments: Celpril (ﬁlm coat of the fungicide Thiram); PAT (primed advance
treatment); TACH (pelletized seed with the fungicide Tachigaren added);
PAT+TACH (combines the primed advance treatment and Tachigaren) and Plain
Pellet (Celpril treated seed covered in a pellet without further treatment).

Laboratory tests used to evaluate seed quality and vigor included the
standard pleated germination test counted at 5 and 10 d, the 5- and 10—d cold
test, the 3- and 6-d high moisture cold test, the 2- and 4-d standard accelerated
aging test, the 2-and 4-d accelerated aging test incubated over NaBr, the 5- and
10-d sand test and the bulk conductivity test. Field emergence data were
collected at Saginaw, Ingham and Huron counties in 1998 and in Saginaw and

Ingham counties in 1999.

I. Laboratory Tests

Signiﬁcant correlations between the pleated germination and cold test

results occurred in Exp. 1 during both years. This conﬁrmed the potential of

79

these tests to differentiate within a wide range of seed quality as that used in
Exp. 1. Furthermore, the high correlations between the 5-d and 10-d counts for
the pleated germination and cold tests suggest that the 5-d germination count
may be sufﬁcient. Although signiﬁcant correlation also occurred between results
of the sand and accelerating aging tests over sodium bromide for Exp.1 in 1998
and Exp. 2, the correlations were not as high as those found between the cold
and pleated germination test. Poor correlations were also found for the high
moisture cold test, the standard accelerated aging test and the conductivity test

for both experiments.

ll. Relationship Between Laboratory Test and Field Emergence

Results of pleated germination and cold tests were signiﬁcantly correlated
with ﬁeld emergence for all three experiments when using the simple coefﬁcients
of determination. Cold test results were better correlated with ﬁeld emergence
under lower soil temperature conditions like those at the early planting in Exp. 2
in 1999. However, the cold test also performed well as soil temperatures
increased. On the other hand, the high moisture cold test performed no better
than the standard cold test. Correlations between the sand test results and ﬁeld
emergence were the third highest for Exp.1 in 1998. However, such correlations
were not achieved during any subsequent year or experiment. Results of
accelerated aging tests over water and sodium bromide were not signiﬁcantly

correlated with ﬁeld emergence. With the exception of the early planting for Exp.

80

2 in 1999, conductivity test results were also poorly correlated with ﬁeld
emergence.

Multiple stepwise coefﬁcients of determination were calculated for each
location in Exp.1 and 2, with each equation consisting of a different set of
independent variables (laboratory tests). For most equations, the coefﬁcients of
the variables on ﬁeld emergence accounted for over 49.0% of the variability. The
cold and pleated germination tests appeared in most of these equations.

However, when these two variables were regressed on ﬁeld emergence for all

locations on both experiments, the resulting R2 values were usually lower and

did not signiﬁcantly contribute to the equations.

lll. Inﬂuence of Seed Size on Germination and Field Emergence

In the majority of the comparisons, seed size was not signiﬁcantly
associated with the laboratory test results. However, a masking effect of seed
size was observed in the conductivity test. Overall, seed size in 1998 and early
planting in 1999 did not signiﬁcantly inﬂuence ﬁeld emergence. However, at the
late planting in 1999, most of the comparisons produced signiﬁcant differences in
percent stand establishment between seed size two and four. Although, these
differences were signiﬁcant, no relative ranking among seed sizes was made
because of inconsistencies in performance of different seed sizes among

varieties.

81

IV. Inﬂuence of §eed Treatments on Field Emergence
Two planting dates were selected in 1998 (4/15 and 5/15) to evaluate the

inﬂuence of planting date on the emergence of the treated seed. In the early
planting, all seed treatments produced higher emergence than the standard
Celpril treatment. However, the priming advanced treatment (PAT) induced more
rapid emergence than any of the other treatments. Celpril treated seed always
produced the lowest emergence throughout all the counts. Again, in the late
planting, seedlings from PAT treated seed emerged earlier than those from other
treatments. However, the other three seed treatments (Celpril, TACH, PAT +
TACH, Plain) induced similar emergence to that of PAT treated seed at later
counts. On the other hand, Celpril coated seed was not as effective as PAT in
controlling soilborne pathogens, especially at the late planting. Although a
similar stand establishment trend occurred at both planting dates, the overall
mean emergence was signiﬁcantly much lower at the late planting date.

In 1999 all treatments were planted at the same time, however, three sites
with varying Aphanomyces spp. indices were chosen (low, medium, high). In
Site 1 the seedling emergence was not signiﬁcantly different among the seed
treatments for the ﬁrst three counts. At the last count, signiﬁcant differences
occurred between Plain pelleted seed and the PAT + TACH. The overall
emergence for all seed treatments on Site 1 was high. At Site 2, where the
organism index was medium, the overall emergence was lower than that at Site 1
for all five seed treatments. Contrary to the ﬁndings in Site 1, the lowest

emergence occurred for the PAT + TACH treated seed. At the last count, the

82

highest ﬁeld emergences occurred for both Celpril and the Plain pelleted seed.
However, when Celpril was compared in a high organism pressure environment
like that on Site 3, the incidence of seedling survival was as low as that of the
Plain pelleted seed, indicating that Thiram alone (fungicide contained in Celpril)
does not perform well under severe disease conditions. However, when
combined with a treatment that will speed up the germination with a fungicide like
PAT + TACH, the resulting stand can be signiﬁcantly improved under such

severe disease conditions. This conﬁrms the effect of TACH (Tachigaren) in

controlling Aphanomyces spp.

83

CONCLUSIONS

The following conclusions can be drawn from these studies:

1. No single laboratory test can predict ﬁeld emergence under all
environments, because of the wide range of favorable and unfavorable soil and
temperature conditions.

2. Variation in emergence under different planting conditions is likely
due to varying environmental conditions, including biotic factors, rather than to
intrinsic differences in seed quality/vigor. Even aging treatments, which are
intended to test physiological vigor, failed to result in higher coefﬁcients of
determination between laboratory test results and ﬁeld emergence.

3. The use of the pleated germination test plus the cold germination
test should give the best indication of potential ﬁeld emergence under most ﬁeld
conditions found in Michigan.

4. A 5—d germination count may be sufﬁcient for the pleated
germination and cold test.

5. No consistent association was found between seed size,
germination and ﬁeld emergence.

6. Celpril treated seed performed as well as other seed
treatments/enhancements under low and medium disease environments at the

late planting date.

7. PAT (Priming Advance Treatment) resulted in a lower incidence of
soilborne diseases by reducing the period during which seedlings are susceptible
to the pathogens.

8. PAT + TACH could be used to provide control over soilborne
pathogens when ﬁeld infestation is high.

Overall, these studies showed conclusively that there are no intrinsic
problems with seed quality/vigor in the sugar beet industry in Michigan. The
study also showed that emergence problems in sugar beet seed are unlikely to
be avoided by the application of vigor tests. Therefore, more attention should be
given to studying soil and environmental factors which limit germination and
stand establishment. Rather than seed quality, the problem appears to be abiotic
and biotic factors in the soil that affect germination and stand establishment,
even with the use of high quality seed. Agronomic practices such as crop
rotation should be continued to help minimize seedling loss from pathogens.
Finally, seed treatment strategies should be continued to help avoid seedling loss
during and immediately following germination. This, along with appropriate
agronomic practices and the continued use of high quality seed should help keep

the need for replanting to a minimum.

85

APPENDIX

86

Table A1.

Table A2.

Analysis of variance for the pleated germination, cold and
sand test results for Exp. 1 (Seed Quality), 1998 as Inﬂuenced
by variety, time of count and replication.

 

Pleated Test Cold Teg Sang ng

 

M gr F-value Pr>F F-yglue Pr>F E-value Pr>F
Variety 19 76.08 <.0001' 1013.40 <.0001* 169.41 <.0001*

Time 1 305.93 <.0001" 56.85 <.0048* 1846.27 <.0001"
Rep 3 0.36 0.7791 6.38 0.0811 31.64 0.0090‘
Var‘Time 19 54.76 <.0001* 4.19 <.0001" 7.53 <.0001*

 

* Signiﬁcant at the 0.05 probability level

Analysis of variance for the accelerated aging test results for

Exp. 1 (Seed Quality), 1998 as inﬂuenced by variety, time of
count and replication.

 

Accelerated Aging

 

 

m: Hal—Br
m d_f m BEE m Pr>F
Variety 19 86.22 <.0001* 9.94 <.0001*
Time 1 13053.1 00056" 2292.8 0.0043-
Rep 3 10.56 0.1900 51.18 0.0884
Var‘Time 19 7.90 <.0001* 2.00 0.0699

 

* Significant at the 0.05 probability level

87

Table A3.

Slicing procedure for the interaction effect between variety
and time of count for the pleated germination test In Exp. 1

(Seed Quality), 1998.

 

 

 

Sliced by Time
ime g1 F-Valug £321:
10 days 19 33.09 <.0001"
5 days 19 112.96 <.0001"
Sliced by Varlety
198$! 91 E13812 ERE
1 1 2.89 0.0942
2 1 0.41 0.5261
3 1 1.63 0.2071
4 1 0.41 0.5261
5 1 7.64 0.0076"
6 1 10.17 0.0023"
9 1 0.05 0.8324
10 1 13.06 0.0006"
11 1 0.05 0.8324
14 1 5.47 0.0227"
15 1 6.51 0.0133"
16 1 2.89 0.0942
17 1 0.41 0.5261
18 1 1200.41 <.0001"
20 1 35.42 <.0001"
21 1 6.51 0.0133"
52 1 19.92 <.0001"
54 1 16.31 00002"
56 1 14.64 0.0003"
57 1 1.63 0.2071

 

* Signiﬁcant at the 0.05 probability level

88

Table A4.

Slicing procedure for the interaction effect between variety
and time of count for the cold test in Exp. 1 (Seed Quality),

 

 

 

1998.
Sliced by Time
11m if - al P_r>.E
10 days 19 469.41 <.0001"
5 days 19 548.19 <.0001"
Sliced by Variety
1892!! 9.! ._¥_L£F- a U BEE
1 1 14.18 00004"
2 1 2.27 0.1375
3 1 0.14 0.7079
4 1 0.00 1.0000
5 1 2.27 0.1375
6 1 2.27 0.1375
9 1 0.14 0.7079
10 1 6.95 0.0108"
11 1 0.14 0.7079
14 1 3.55 0.0648
15 1 5.11 0.0277"
16 1 1.28 0.2633
17 1 0.57 0.4544
18 1 56.74 <.0001"
20 1 23.97 <.0001"
21 1 0.57 0.4544
52 1 31.91 <.0001"
54 1 9.08 0.0039"
56 1 0.14 0.7079
57 1 0.57 0.4544

 

* Signiﬁcant at the 0.05 probability level

89

Table A5. Slicing procedure for the Interaction effect between variety
and time of count for the accelerated aging test in Exp. 1 (Seed
Quality), 1998.

 

 

 

Sliced by Time
Iim_e d_f F-Value ﬂ>_F
2 days 19 40.84 <.0001"
4 days 19 53.28 <.0001"
Sliced by Variety
Man's-mt m E___1;_-Val e M
1 1 37.06 <.0001"
2 1 1.42 0.2483
3 1 85.81 <.0001"
4 1 123.57 <.0001"
5 1 60.96 <.0001"
6 1 88.28 <.0001"
9 1 54.92 <.0001"
10 1 8.48 0.0090"
11 1 58.91 <.0001"
14 1 76.29 <.0001"
15 1 76.29 <.0001"
16 1 45.55 <.0001"
17 1 52.98 <.0001"
18 1 0.16 0.6958
20 1 12.77 0.0020"
21 1 30.89 <.0001"
52 1 29.44 <.0001"
54 1 14.73 0.0011"
56 1 16.83 0.0006"
57 1 13.73 0.0015"

 

* Signiﬁcant at the 0.05 probability level

90

Table A6.

Slicing procedure for the interaction effect between variety
and time of count for the sand test in Exp. 1 (Seed Quality),

 

 

 

1 998.
Sliced by Time
M9. g E-yalue Egli
10 days 19 62.38 <.0001"
5 days 19 114.56 <.0001"
Sliced by Variety
riet gt F-yglue Egﬁ
1 1 27.65 <.0001"
2 1 3.79 0.0564
3 1 6.41 0.0141"
4 1 9.71 0.0029"
5 1 38.84 <.0001"
6 1 18.36 <.0001"
9 1 0.34 0.5614
10 1 12.29 0.0009"
11 1 8.53 0.0050"
14 1 15.17 0.0003"
15 1 43.84 <.0001"
16 1 3.07 0.0850
17 1 20.06 <.0001"
18 1 155.35 <.0001"
20 1 23.70 <.0001"
21 1 43.84 <.0001"
52 1 54.77 <.0001"
54 1 83.78 <.0001"
56 1 41.30 <.0001"
57 1 46.46 <.0001"

 

" Signiﬁcant at the 0.05 probability level

91

Table A7. Analysis of variance for the pleated germination, cold, high
moisture cold and conductivity test results for Exp. 1 (Seed
Quality), 1999 as inﬂuenced by variety, time of count and

 

replication.
Cold High Coggggtiyity
Pleated Test Cold Test Moisture Teg lest

 

 

_S_0_ULC_§ 0: film _E_r_>_E F-value Pr>F F-value Pr>F F-yalge Pr>F

Variety 19 11.31 <.0001* 5.65 0.000* 2.64 <0.202* 42.02 <.0001*

Time 1 42.34 <.0001* 5.26 0.0818 59.99 <.0001* NIA NIA
Rep 3 2.16 0.1032 0.93 0.9840 2.90 0.1047 0.23 0.8718
Var"Time 19 1.31 0.2168 0.29 0.1990 0.56 0.7692 NIA NIA

 

* Signiﬁcant at the 0.05 probability level
NIA = Effect Non-applicable for the test

Table A8. Analysis of variance for the pleated germination, cold, high
moisture cold and sand test results for Exp. 2 (Seed Size) as
inﬂuenced by variety, seed size, time of count and replication.

 

Cold High Sand
Pleated Test Cold Test Moisture Test Test

 

 

Source 91 F-yglue P1>E F-value Pr>F F-valug Pr>F E-valgg Pr>F

Variety 2 6.48 0.0317* 4.97 0.0534 0.97 0.5080 12.27 00076"
Size 2 0.50 0.6077 0.30 0.7459 1.50 0.2543 22.78 <.0001*
Time 1 25.98 <.0001“ 3.17 0.0818 46.41 <.0001* 131.47 <.0001*
Rep 3 0.78 0.5468 0.05 0.9840 0.51 0.5488 0.17 0.9099

Var‘Size 4 2.94 0.0307* 1.57 0.1990 0.56 0.6937 1.80 0.1446

Val‘Time 2 0.36 0.6978 0.42 0.6619 1.28 0.3077 8.78 00006"

 

" Significant at the 0.05 probability level

92

Table A9.

Table A10.

Analysis of variance for the pleated germination, cold and
sand test results for Exp. 2 (Seed Size) as inﬂuenced by
variety, seed size, time of count and replication.

 

Water Nagr Conductivity lg

 

Source df F-value Pr>F F-value Pr>F F-value P2P
Variety 2 23.05 <.0001" 18.83 <.0001" 53.51 <.0001"
2

Size 2.01 0.1451 5.22 0.0089' 38.55 <.0001'
Time 1 452.59 0.0002* 24573.8 <.0001' NIA N/A
Rep 3 2.41 0.2449 13.91 0.0289" 0.87 0.4744
VaI‘Size 4 2.39 0.0642 2.40 0.0628 2.39 0.0892
Var"l’ime 2 19.59 <.0001" 4.23 0.0203“ NIA NIA

 

" Signiﬁcant at the 0.05 probability level
NIA = Effect Non-applicable for the test

Slicing procedure for the interaction effect between variety
and seed size for the pleated germination test in Exp. 2 (Seed
Size).

 

 

 

Sliced by Size

S129 g: F-Value P_r>_E

2 2 6.21 0.0041"
3 2 3.47 0.0397*
4 2 5.07 0.0103"
Sliced by Variety

m 91 E-yalue 32E
ACH503 2 1.04 0.3604
ACH555 2 0.25 0.7790
ACH648 2 5.08 00103"

 

" Signiﬁcant at the 0.05 probability level

93

Table A1 1 .

Table A1 2.

 

 

 

Slicing procedure for the interaction effect between variety
and germination time for the sand test in Exp. 2 (Seed Size).
Sliced by Time
lime 01 - Iue P_r>E
10 days 2 1.88 0.1641

5 days 2 19.96 <.0001"
Sliced by Variety
M31320: 9.1 F- In E_I>_F.
ACH503 1 37.28 <.0001*
ACH555 1 96.17 <.0001*
ACH648 1 15.58 0.0003*

 

* Signiﬁcant at the 0.05 probability level

Slicing procedure of the interaction effect between variety and
aging time for the accelerated aging test In Exp. 2 (Seed Size).

 

 

 

Sliced by Time

1er 9.! F- ue Eri

2 days 2 0.58 0.5626
4 days 2 42.06 <.0001*
Sliced by Variety

My 01 MM. M
ACH503 1 260.45 <.0001*
ACH555 1 62.60 <.0001*
ACH648 1 204.85 <.0001"

 

" Signiﬁcant at the 0.05 probability level

94

Table A13. Slicing procedure of the interaction effect between variety and
time of aging for the accelerated aging test over NaBr in Exp. 2

Table A14.

 

 

 

(Seed Size).

Sliced by Time

Iim_e 9! 51/2016 212E

2 days 2 2.97 0.0610
4 days 2 20.09 <.0001"
Sliced by Variety

M! 9.! living BEE
ACH503 1 1380.32 <.0001"
ACH555 1 1040.48 <.0001"
ACH648 1 1228.80 <.0001"

 

* Signiﬁcant at the 0.05 probability level

Analysis of variance for pleated germination and cold test
results for Exp. 3 (Seed Enhancement), 1998 as inﬂuenced by

treatment, time of count and replication.

 

 

Pleated Test M
M d_f EM Er>_F fialu_e BEE
Treatment 4 42.26 <.0001" 3.79 0.0204"
Time 1 12.96 0.0026" 9.22 0.0083"
Rep 3 0.99 0.4223 1 .24 0.3306
Treat'Time 4 1 .55 0.2341 0.45 0.8087

 

* Signiﬁcant at the 0.05 probability level

95

Table A15. Analysis of variance for pleated germination and cold test
results for Exp. 3 (Seed Enhancement), 1999 as inﬂuenced by
treatment, time of count, and replication.

 

 

Pleated Test mm
M £1! ELM BEE M199 EJZE
Treatment 4 12.49 0.0002" 7.40 0.0030"
Time 1 47.66 <.0001" 9.14 0.0106"
Rep 3 1 .31 0.3155 0.60 0.6297
Treat"Time 4 2.37 0.1110 1.29 0.3294

 

" Signiﬁcant at the 0.05 probability level

Table A16. Multiple comparison and mean separation for the conductivity
test in Exp. 2 (Seed Size).

 

 

Variety Size LSMEAN SE OF t Pr>|t| LetGrp
ACH648 2 621.78 17.94 18 64.65 0.0001 A
ACH648 3 525.23 17.94 18 29.27 0.0001 8
ACH648 4 459.72 17.94 18 25.62 0.0001 C
ACH503 2 653.69 17.94 18 36.43 0.0001 A
ACH503 3 535.47 17.94 18 29.84 0.0001 8
ACH503 4 507.13 17.94 18 28.26 0.0001 8
ACH555 2 462.75 17.94 18 25.79 0.0001 A
ACH555 3 403.81 17.94 18 22.50 0.0001 B
ACH555 4 398.85 17.94 18 22.23 0.0001 8

 

 

 

 

Table A1 7. Multiple comparison and mean separation for the different
planting dates and stand counts conducted in Exp. 3 (Seed
Enhancement), 1998.

TLANTITIG TMT DAP LSMEAN sE [TIE t Pr>|t| LetGrp
Early Celpril 1 1 0.45 2.69 390 0.17 0.8686 8
Early PAT 11 19.33 2.69 390 7.19 0.0001 A
Early PATACH 1 1 5.44 2.69 390 2.03 0.0435 8
Early Plain 1 1 2.1 1 2.69 390 0.79 0.4325 8
Early TACH 1 1 1 .1 1 2.69 390 0.41 0.6794 8
Early Celpril 13 11.34 2.69 390 4.22 0.0001 0
Early PAT 13 40.33 2.69 390 15.01 0.0001 A
Early PATACH 13 27.22 2.69 390 10.13 0.0001 8
Early Plain 13 19.44 2.69 390 7.23 0.0001 C
Early TACH 13 12.67 2.69 390 4.71 0.0001 CD
Early Celpril 16 20.33 2.69 390 7.57 0.0001 D
Early PAT 16 46.11 2.69 390 17.16 0.0001 A
Early PATACH 16 29.78 2.69 390 1 1 .08 0.0001 BC
Early Plain 16 34.33 2.69 390 12.77 0.0001 8
Eany TACH 16 26.22 2.69 390 9.76 0.0001 CD
Early Celpril 19 32.22 2.69 390 11 .99 0.0001 C
Eany PAT 19 50.22 2.69 390 18.69 0.0001 A
Early PATACH 19 38.45 2.69 390 14.30 0.0001 BC
Early Plain 19 44.56 2.69 390 16.58 0.0001 AB
Eaﬂy TACH 19 40.33 2.69 390 15.01 0.0001 8
Early Celpril 22 48.11 2.69 390 17.90 0.0001 8
Early PAT 22 57.89 2.69 390 21.54 0.0001 A
Early PATACH 22 45.55 2.69 390 16.95 0.0001 8
Early Plain 22 58.89 2.69 390 21.91 0.0001 A
Early TACH 22 50.22 2.69 390 18.69 0.0001 8

 

97

 

 

Table A 17. Cent.

PLANTING TMT DAP LSMEAN 5? DP; t Pr>|t| LetGrp
Early Celpril 28 49.67 2.69 390 18.48 0.0001 6
Early PAT 28 57.56 2.69 390 21.41 0.0001 A
Early PATACH 28 49.45 2.69 390 18.40 0.0001 B
Early Plain 28 59.89 2.69 390 22.28 0.0001 A
Early TACH 28 53.22 2.69 390 19.80 0.0001 Ae
Early Celpril 44 47.67 2.69 390 17.74 0.0001 c
Early PAT 44 58.33 2.89 390 20.96 0.0001 AB
Early PATACH 44 49.22 2.69 390 18.31 0.0001 ec
Early Plain 44 58.22 2.69 390 21.66 0.0001 A
Early TACH 44 54.67 2.69 390 20.34 0.0001 ABC
Early Celpril 49 45.89 2.69 390 17.07 0.0001 c
Early PAT 49 54.44 2.69 390 20.26 0.0001 AB
Early PATACH 49 48.89 2.69 390 18.19 0.0001 BC
Early Plain 49 54.11 2.69 390 20.13 0.0001 AB
Early TACH 49 53.78 2.69 390 20.01 0.0001 AB
Late Celpril 19 2.58 2.69 390 0.95 0.3427 B
Late PAT 19 10.78 2.69 390 4.01 0.0001 A
Late PATACH 19 5.22 2.69 390 1.94 0.0528 AB
Late Plain 19 5.78 2.69 390 2.15 0.0322 A6
Late TACH 19 1.89 2.69 390 0.70 0.4827 6
Late Celpril 24 3.89 2.69 390 1.45 0.1488 6
Late PAT 24 12.11 2.69 390 4.51 0.0001 A
Late PATACH 24 7.89 2.69 390 2.94 0.0035 AB
Late Plain 24 7.00 2.69 390 2.60 0.0096 AB
Late TACH 24 3.89 2.69 390 1.45 0.1488 6

 

98

 

 

 

Table A 17. Cont.

_PLANTTNG ﬁﬁ bAP LSMEAN SE OF t Pr>|t| Letcrp
Late Celpril 31 27.45 2.69 390 10.21 0.0001 A
Late PAT 31 28.58 2.69 390 1062 0.0001 A
Late PATACH 31 28.00 2.69 390 10.42 0.0001 A
Late Plain 31 28.89 2.89 390 10.75 0.0001 A
Late Proprim 31 34.78 2.69 390 12.94 0.0001 A
Late TACH 31 27.56 2.69 390 10.25 0.0001 A
Late Celpril 34 22.22 2.69 390 8.27 0.0001 B
Late PAT 34 24.45 2.69 390 9.09 0.0001 AB
Late PATACH 34 22.33 2.69 390 8.31 0.0001 8
Late Plain 34 25.33 2.69 390 9.43 0.0001 AB
Late Proprim 34 30.45 2.69 390 11.83 0.0001 A
Late TACH 34 20.22 2.69 390 7.52 0.0001 6
Late Celpril 38 26.34 2.69 390 9.80 0.0001 A
Late PAT 38 26.45 2.69 390 9.84 0.0001 A
Late PATACH 38 25.11 2.69 390 9.34 0.0001 A
Late Plain 38 27.45 2.69 390 10.21 0.0001 A
Late Proprim 38 29.56 2.69 390 11.00 0.0001 A
Late TACH 38 22.89 2.69 390 8.52 0.0001 A

 

99

Table A18. Multiple comparison and mean separation for the different
sites and stand counts conducted in Exp. 3 (Seed
Enhancement), 1999.

 

 

 

ﬁT‘E WT DAP LSMEAN sE DF t Pr>|t| LetGrp
Low Celpril 9 70.75 4.91 195 14.41 0.0001 A
Low PAT 9 75.25 4.91 195 15.32 0.0001 A
Low PATACH 9 68.00 4.91 195 13.85 0.0001 A
Low Plain 9 78.25 4.91 195 15.94 0.0001 A
Low TACH 9 74.25 4.91 195 15.12 0.0001 A
Low Celpn‘l 14 70.50 4.91 195 14.36 0.0001 A
Low PAT 14 73.50 4.91 195 14.97 0.0001 A
Low PATACH 14 66.00 4.91 195 13.44 0.0001 A
Low Plain 14 78.25 4.91 195 15.94 0.0001 A
Low TACH 14 76.25 4.91 195 15.53 0.0001 A
Low Celpril 17 70.75 4.91 195 14.41 0.0001 A
Low PAT 17 70.75 4.91 195 14.41 0.0001 A
Low PATACH 17 65.75 4.91 195 13.39 0.0001 A
Low Plain 17 78.75 4.91 195 16.04 0.0001 A
Low TACH 17 75.75 4.91 195 15.43 0.0001 A
Low Celpril 21 70.00 4.91 195 14.26 0.0001 AB
Low PAT 21 69.25 4.91 195 14.10 0.0001 AB
Low PATACH 21 64.50 4.91 195 13.14 0.0001 B
Low Plain 21 78.75 4.91 195. 16.04 0.0001 A
Low TACH 21 75.50 4.91 195 15.38 0.0001 AB
Medium Celpril 9 49.00 4.91 195 9.98 0.0001 A
Medium PAT 9 41.50 4.91 195 8.45 0.0001 A
Medium PATACH 9 25.25 4.91 195 5.14 0.0001 B
Medium Plain 9 50.50 4.91 195 10.28 0.0001 A
Medium TACH 9 37.25 4.91 195 7.59 0.0001 AB
Medium Celpril 14 57.75 4.91 195 11.76 0.0001 AB
Medium PAT 14 45.75 4.91 195 9.32 0.0001 BC
Medium PATACH 14 32.25 4.91 195 8.57 0.0001 c
Medium Plain 14 60.00 4.91 195 12.22 0.0001 A
Medium TACH 14 49.50 4.91 195 10.08 0.0001 AB

 

100

 

 

 

Table A18. Cont.
sﬁ TMT DAP LsM'EAN s? DF t Pr>|t| LetGrp
Medium Celpril 17 59.25 4.91 195 12.07 0.0001 A
Medium PAT 17 44.50 4.91 195 9.06 0.0001 BC
Medium PATACH 17 32.25 4.91 195 6.57 0.0001 c
Medium Plain 17 60.00 4.91 195 12.22 0.0001 A
Medium TACH 17 50.00 4.91 195 10.18 0.0001 AB
Medium Celpril 21 63.50 4.91 195 12.93 0.0001 A
Medium PAT 21 45.75 4.91 195 9.32 0.0001 ec
Medium PATACH 21 33.50 4.91 195 6.82 0.0001 c
Medium Plain 21 62.50 4.91 195 12.73 0.0001 A
Medium TACH 21 51.50 4.91 195 10.49 0.0001 AB
High Celpril 9 54.00 4.91 195 11.00 0.0001 8
High PAT 9 58.50 4.91 195 11.91 0.0001 AB
High PATACH 9 66.50 4.91 195 13.54 0.0001 AB
High Plain 9 68.25 4.91 195 13.90 0.0001 A
High TACH 9 66.25 4.91 195 13.49 0.0001 AB
High Celpril 14 46.75 4.91 195 9.52 0.0001 AB
High PAT 14 39.00 4.91 195 7.94 0.0001 8
High PATACH 14 58.25 4.91 195 11.86 0.0001 A
High Plain 14 47.50 4.91 195 9.67 0.0001 AB
High TACH 14 53.50 4.91 195 10.90 0.0001 A
High Celpril 17 26.75 4.91 195 5.45 0.0001 BC
High PAT 17 23.00 4.91 195 4.68 0.0001 c
High PATACH 17 52.25 4.91 195 10.64 0.0001 A
High Plain 17 31.00 4.91 195 6.31 0.0001 60
High TACH 17 38.50 4.91 195 7.84 0.0001 B
High Celpril 21 14.75 4.91 195 3.00 0.0001 B
High PAT 21 14.75 4.91 195 3.00 0.0001 a
High PATACH 21 41.00 4.91 195 8.35 0.0001 AB
High Plain 21 20.25 4.91 195 4.12 0.0001 B

 

101

Table A19. Daily maximum and minimum soil temperatures (°C) and
precipitation (mm) at the three ﬁeld testing locations in 1998.

 

 

 

Misteguay Metea Kilmanaﬂ
Date m. ML 2m.- M m. 0m M... MLn. 01m
04/01 10.2 8.2 3.8 13.3 12.2 19.6 16.1 3.9 28.2
04/02 8.4 7.3 0.8 12.8 10.0 9.9 16.1 3.9 5.8
04/03 7.3 6.3 8.9 8.9 0.8 6.7 2.8 1.3
04/04 8.7 5.3 7.2 9.4 0.5 7.2 1.1
04/05 9.2 4.4 8.3 6.1 7.8 -1.7
04/06 9.7 4.5 9.4 6.7 7.2 -50
04/07 10.1 5.4 10.0 7.2 11.1 -50
04/08 8.9 6.8 6.9 10.0 8.3 10.2 12.8 0.0
04/09 6.8 6.0 6.1 8.3 4.1 5.0 3.9 7.1
04/10 9.0 4.5 8.9 6.7 5.3 8.3 0.6
04/11 9.9 4.7 7.8 6.1 8.3 -50
04/12 10.4 6.4 10.0 7.2 15.6 -50
04/13 11.4 8.3 11.1 8.3 20.6 4.4
04/14 11.5 9.9 1.3 10.6 9.4 0.8 21.1 9.4 T
04/15 10.8 8.7 11.1 10.6 2.5 12.8 3.3 8.9
04/16 11.3 8.1 13.2 10.6 10.0 1.0 10.0 2.2
04/17 10.4 7.4 11.7 10.0 7.4 16.7 1.1 13.7
04/18 11.3 6.2 10.6 8.9 0.5 9.4 1.7
04/19 11.8 8.1 11.1 8.9 17.2 3.3
04/20 12.8 7.6 11.1 9.4 13.3 0.6
04/21 12.6 8.8 12.2 9.4 16.1 ' 0.6
04/22 14.3 8.9 12.2 11.1 16.1 1.7
04/23 14.9 9.3 13.3 11.1 17.8 1.7
04/24 14.2 10.2 13.3 10.6 18.9 2.2
04/25 13.1 9.2 13.3 11.1 17.2 1 1
04/26 11.9 9.4 13.3 10.6 24.1 10.0 1.7
04/27 11.8 6.8 12.2 9.4 10.2 4.4 -1.7
04/28 13.1 6.9 12.2 8.9 9.4 -3.9
04/29 12.0 8.3 13.3 9.4 15.6 -3.3
04/30 13.7 10.2 1.5 12.8 10.6 0.3 16.7 0.6 T
05/01 15.5 12.3 13.3 12.8 17.3 21.1 8.3
05/02 14.3 12.4 15.6 13.3 21.8 16.7 9.4 8.1
05/03 15.2 11.6 11.7 11.7 1.5 13.9 7.2 1.5
05/04 15.9 11.6 15.0 14.4 1.3 20.0 7.2
05/05 16.9 11.7 16.7 13.9 2.5 21.1 7.8
05l06 17.7 13.8 17.2 13.9 23.9 9.4 0.5
05/07 17.9 14.6 18.3 15.6 25.0 10.6 1.8
05I08 16.8 14.8 26.9 18.3 16.7 0.3 23.3 10.6
05/09 16.5 13.4 8.9 17.2 15.6 1.3 18.3 7.2
05/10 17.2 12.4 18.3 15.6 15.6 6.1
05/11 15.9 13.8 17.8 15.0 20.6 6.1 2.5
05112 18.3 14.2 17.2 15.6 1.8 14.4 11.7 4.1
05/13 19.1 15.3 17.8 15.0 2.3 17.8 12.2
05/14 21.2 15.2 19.4 16.1 25.0 9.4
05/15 21.8 16.1 21.1 16.7 26.7 10.0
05/16 21.2 18.5 21.7 18.9 31.7 15.6

102

Table A19. Cont.

 

 

 

Misteguay Metea Kilmanagh
E112 M. m 2010. M. 1m 0m. MA. M10. 2180..
05117 21.3 16.4 21.7 18.9 27.2 15.6
05118 21.3 16.8 21.7 18.9 27.8 13.9 T
05119 22.2 17.6 21.7 18.9 31.1 15.0
05120 21.9 17.8 22.2 18.9 32.2 12.8 0.5
05121 20.1 16.3 22. 2 19.4 25.6 8.9
05122 18.8 14.4 21.7 18.3 15.0 2.2
05123 19.0 13.5 21.1 17.2 17.2 2.8
05124 17.4 14.3 2.5 21.1 16.7 21.1 5.6
05125 15.6 14.3 4.8 18.3 17.8 3.8 22.8 11.1 3.6
05126 19.2 12.4 17. 8 15. 6 0.3 17.2 9.4 9.4
05127 20.4 14.6 20. 6 15. 0 19.4 7.2
05128 19.8 15.7 21. 7 17. 8 26.1 10.0
05129 20.7 17.4 0.8 21.1 18.3 28.3 15.0 1.8
05130 21.4 16.4 21.7 19.4 26.7 7.2
05131 19.8 18.2 5.8 23.3 19.4 15.2 22.8 10.0 0.5
06/01 19.4 14.2 22.8 18.3 23.3 2.8 2.0
06102 19.1 16.3 22.2 18.3 20.0 5.6
06103 17.6 14.2 21.7 17.8 26.1 5.0
06104 17.6 12.9 19.4 16.1 15.6 3.9 T
06105 16.2 13.1 19.4 16.1 17.8 1.1
06106 15.4 12.3 17.8 15.6 13.9 3.3
06107 16.6 12.4 16.7 15.0 15.6 7.2 0.3
06108 17.9 12.4 17.8 15.0 17.2 3.9
06109 16.5 13.9 1.0 18. 9 15. 0 19.4 3.9
06110 15.7 14.3 5.8 17. 8 16. 1 9.4 21.1 10.0 T
06111 17.2 14.9 5.6 18.3 16.1 0.5 19.4 12.2 0. 5
06112 19.9 16.8 1.0 18.3 16.7 7.1 22.2 14.4 18. 3
06113 19.4 16.9 2.5 22.2 18.3 9.4 27.2 14.4
06114 21.6 16.1 21.7 18. 9 0.5 19.4 12.2 3.6
06115 23.3 17.3 1.3 22. 8 18. 9 24.4 11. 1
06116 23.4 18.6 24. 4 20.6 1.8 24.4 12. 8
06117 23.7 19.1 24.4 21.7 3.6 25.0 14.4
06118 24.7 18.9 24.4 21.1 25.0 13.9
06119 24. 1 20.7 25.0 21.1 26. 1 16.1 1.8
06120 25.4 19.8 26. 1 22.8 31.1 17. 8
06121 25.1 21.1 4.3 26. 1 22. 2 32. 2 18. 9 6.1
06122 25.8 20.3 26.1 23. 3 28.9 19.4
06123 26. 7 22.1 0.5 26.7 23.3 30.0 15.6
06124 26.3 21.8 27.8 25.0 32.8 16.7
06125 26. 9 23.0 27.2 24.4 8.9 33. 9 19.4
06126 27.3 23.7 27.8 23.9 20.8 33.9 16.7
06127 25.7 22.2 5.8 27.8 24.4 1.3 26.7 16.1 1.0
06128 26.5 21.7 26. 7 24. 4 30.0 17.8
06129 26.6 21.7 26. 7 24. 4 0.3 31.7 15. 6 12.2
06130 25.1 22.7 27.8 23.9 0.3 30.0 15. 6

103

Table A20. Daily maximum and minimum soil temperatures ("0) and
precipitation (mm) at the three ﬁeld testing locations in 1999.

 

 

Mistegiay Metea
Date MAX.- Min. 221.0. Mags MEL 020
04101 9.3 8.1 11.0 8.9
04102 10.9 8.4 13.4 9.7
04103 12.8 9.4 15.0 11.3 18.8
04104 12.3 7.9 10.4 13.4 9.5 17.0
04105 9.5 6.6 12.1 7.5 0.3
04106 8.9 7.3 0.8 11.3 8.2 0.3
04107 10.3 6.0 0.3 13.3 6.5
04108 12.6 7.7 15.8 8.9 1.5
04109 11.3 7.4 4.8 12.0 6.8 23.4
04110 8.9 5.4 11.1 5.1
04111 8.1 5.4 21.6 8.0 6.3 7.9
04112 8.8 4.3 11.9 4.9
04113 10.6 4.9 12.5 5.8
04114 11.7 5.9 13.8 6.2
04115 10.4 7.6 10.3 7.9
04116 8.9 7.2 15.0 9.3 7.8 12.7
04117 8.9 6.1 3.6 10.1 7.1 1.3
04118 8.3 6.5 0.8 10.4 7.1 1.3
04119 8.8 6.0 10.9 6.6 2.0
04120 11.0 6.3 12.7 8.0 0.5
04121 9.9 8.0 11.8 9.2
04122 9.3 8.1 39.9 10.9 9.1 50.0
04123 8.1 6.6 17.0 9.1 6.6 27.4
04124 9.5 4.6 11.3 4.8
04125 10.8 5.4 12.9 6.0
04126 12.3 7.1 13.9 7.6
04127 11.4 8.1 13.3 9.0
04128 11.7 7.9 13.6 8.5
04129 12.2 8.1 13.8 8.7
04130 13.1 7.7 14.7 8.5
05101 14.4 8.7 13.3 11.1
05102 14.9 9.8 13.9 10.0
05103 15.8 10.7 14.4 12.8
05104 16.7 11.7 14.4 12.8
05105 15.6 12.9 0.5 15.0 13.9
05106 15.0 13.8 1.3 17.2 15.0 0.3
05107 14.8 12.2 16.1 15.0 1.3
05108 14.2 12.5 3.3 16.1 15.0
05109 14.9 10.7 15.6 13.9 1.0
05110 15.3 10.8 13.9 13.9
05111 15.6 11.2 14.4 13.3
05112 14.4 11.4 5.8
05113 13.3 10.1 15.0 13.3 2.0
05114 14.9 9.8 14.4 13.3
05115 15.7 12.5 1.8 13.9 12.8

104

Table A20. Cont.

05116
0511 7
0511 8
0511 9
05/20
05121
05122
05123
05124
05125
05126
05127
05128
05129
05130
05/31

06101
06102
06103
06104
06105
06106
06107
06108
06109
0611 0
0611 1
0611 2
0611 3
06114
0611 5
0611 6
0611 7
06/1 8
0611 9
06120
06/21
06122
06123
06124
06125
06126
06127
06128
06129
06130

 

Misteguay

16.9 13.4 5.6
18.8 15.3 8.6
17.6 16.3 3.0
17.3 13.5

18.7 12.9

18.7 15.1

17.8 15.8 1.3
16.3 13.4 17.3
15.1 12.3

12.3 11.1 1.8
15.8 10.7

17.6 11.2

19.7 13.4

21.2 15. 2

21.6 17. 0

20.3 18.2 1.3
22.0 18.2 2.5
20.7 18.6 5.3
19.7 16.0

20.3 15.0

21.9 16.9

24. 3 19.8

24.2 20.8

24. 7 20.3 1.0
23. 4 20.3

25.8 20.4

26.2 22.0

25.9 22.0 5.3
24. 7 21.7 8.4
22. 3 20.1 9.9
20. 9 16.6

20.7 17.5

21.2 16.9 1.0
22.5 16. 4

22.0 18.0

22.8 18.3

24. 1 18.6

23. 9 19. 1

24.3 20. 2

23.3 21.6

26.2 20.1

26.3 21.3

25 22.3

25.8 21.9

24.8 20. 9

22.9 19.9

105

Metea

 

M

15.6
16.1
20.0
18.9
18.9
18. 9
18. 9
19. 4
17.2
16.1
13.3
16.1
16.7
18.9
18. 9
19. 4

20.0
21.1
21.1
18.4
21.3
24.5
25. 2
25. 6
24.6
26. 6
26. 9
26.8
24.7
23.3
21.8
20.8
21.2
24.1
23.1
24.8
25.6
25.2
26. 2
24. 5
26.8
27.1
25.8
27.3
24.7
22.7

Mill.

15.6
12.2
16.1
17.2
16.7
16.1
17.2
17.2
16.1

19.5

020.

8.9
18.5
1.3

7.6

0.3
2.8

0.3

0.5
6.6

8.9
0.5

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